Search results for: image guided therapy

Authors: Okhee Woo, Hye Seon Shin

Abstract:

Purpose: To investigate the diagnostic power of digital breast tomosynthesis (DBT) in evaluation of breast microcalcifications and usefulness as a pre-procedural study for stereotactic biopsy in comparison with full-field digital mammogram (FFDM) and FFDM plus magnification image (FFDM+MAG). Methods and Materials: An IRB approved retrospective observer performance study on DBT, FFDM, and FFDM+MAG was done. Image quality was rated in 5-point scoring system for lesion clarity (1, very indistinct; 2, indistinct; 3, fair; 4, clear; 5, very clear) and compared by Wilcoxon test. Diagnostic power was compared by diagnostic values and AUC with 95% confidence interval. Additionally, procedural report of biopsy was analysed for patient positioning and adequacy of instruments. Results: DBT showed higher lesion clarity (median 5, interquartile range 4-5) than FFDM (3, 2-4, p-value < 0.0001), and no statistically significant difference to FFDM+MAG (4, 4-5, p-value=0.3345). Diagnostic sensitivity and specificity of DBT were 86.4% and 92.5%; FFDM 70.4% and 66.7%; FFDM+MAG 93.8% and 89.6%. The AUCs of DBT (0.88) and FFDM+MAG (0.89) were larger than FFDM (0.59, p-values < 0.0001) but there was no statistically significant difference between DBT and FFDM+MAG (p-value=0.878). In 2 cases with DBT, petit needle could be appropriately prepared; and other 3 without DBT, patient repositioning was needed. Conclusion: DBT showed better image quality and diagnostic values than FFDM and equivalent to FFDM+MAG in the evaluation of breast microcalcifications. Evaluation with DBT as a pre-procedural study for breast stereotactic biopsy can lead to more accurate localization and successful biopsy and also waive the need for additional magnification images.

Keywords: DBT, breast cancer, stereotactic biopsy, mammography

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Authors: Rui Du

Abstract:

This paper attempts to assess the impact of a major sporting event —the Super Bowl on the local economies. The identification strategy is to compare the winning and losing cities at the National Football League (NFL) conference finals under the assumption of similar pre-treatment trends. The stock market performances of companies headquartered in these cities are used to capture the sudden changes in local economic activities during a short time span. The exogenous variations in the football game outcome allow a straightforward difference-in-differences approach to identify the effect. This study finds that the post-event trends in winning and losing cities diverge despite the fact that both cities have economically and statistically similar pre-event trends. Empirical analysis provides suggestive evidence of a positive, significant local economic impact of conference final wins, possibly through city image enhancement. Further empirical evidence shows the presence of heterogeneous effects across industrial sectors, suggesting that city image enhancing the effect of the Super Bowl participation is empirically relevant for the changes in the composition of local industries. Also, this study also adopts a similar strategy to examine the local economic impact of Super Bowl successes, however, finds no statistically significant effect.

Keywords: Super Bowl Participation, local economies, city image enhancement, difference-in-differences, industrial sectors

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Authors: N. Ghatwary, A. Ahmed, H. Jalab

Abstract:

In this paper, an approach for the liver tumor detection in computed tomography (CT) images is represented. The detection process is based on classifying the features of target liver cell to either tumor or non-tumor. Fractional differential (FD) is applied for enhancement of Liver CT images, with the aim of enhancing texture and edge features. Later on, a fusion method is applied to merge between the various enhanced images and produce a variety of feature improvement, which will increase the accuracy of classification. Each image is divided into NxN non-overlapping blocks, to extract the desired features. Support vector machines (SVM) classifier is trained later on a supplied dataset different from the tested one. Finally, the block cells are identified whether they are classified as tumor or not. Our approach is validated on a group of patients’ CT liver tumor datasets. The experiment results demonstrated the efficiency of detection in the proposed technique.

Keywords: fractional differential (FD), computed tomography (CT), fusion, aplha, texture features.

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Authors: Maris Eugênia Dela Rosa, Ana Luiza Menegatti Pavan, Marcela De Oliveira, Diana Rodrigues De Pina, Luis Carlos Vulcano

Abstract:

In medical veterinary as well as in human medicine, radiological study is essential for a safe diagnosis in clinical practice. Thus, the quality of radiographic image is crucial. In last year’s there has been an increasing substitution of image acquisition screen-film systems for computed radiology equipment (CR) without technical charts adequacy. Furthermore, to carry out a radiographic examination in veterinary patient is required human assistance for restraint this, which can compromise image quality by generating dose increasing to the animal, for Occupationally Exposed and also the increased cost to the institution. The image optimization procedure and construction of radiographic techniques are performed with the use of homogeneous phantoms. In this study, we sought to develop a homogeneous phantom of canine chest to be applied to the optimization of these images for the CR system. In carrying out the simulator was created a database with retrospectives chest images of computed tomography (CT) of the Veterinary Hospital of the Faculty of Veterinary Medicine and Animal Science - UNESP (FMVZ / Botucatu). Images were divided into four groups according to the animal weight employing classification by sizes proposed by Hoskins & Goldston. The thickness of biological tissues were quantified in a 80 animals, separated in groups of 20 animals according to their weights: (S) Small - equal to or less than 9.0 kg, (M) Medium - between 9.0 and 23.0 kg, (L) Large – between 23.1 and 40.0kg and (G) Giant – over 40.1 kg. Mean weight for group (S) was 6.5±2.0 kg, (M) 15.0±5.0 kg, (L) 32.0±5.5 kg and (G) 50.0 ±12.0 kg. An algorithm was developed in Matlab in order to classify and quantify biological tissues present in CT images and convert them in simulator materials. To classify tissues presents, the membership functions were created from the retrospective CT scans according to the type of tissue (adipose, muscle, bone trabecular or cortical and lung tissue). After conversion of the biologic tissue thickness in equivalent material thicknesses (acrylic simulating soft tissues, bone tissues simulated by aluminum and air to the lung) were obtained four different homogeneous phantoms, with (S) 5 cm of acrylic, 0,14 cm of aluminum and 1,8 cm of air; (M) 8,7 cm of acrylic, 0,2 cm of aluminum and 2,4 cm of air; (L) 10,6 cm of acrylic, 0,27 cm of aluminum and 3,1 cm of air and (G) 14,8 cm of acrylic, 0,33 cm of aluminum and 3,8 cm of air. The developed canine homogeneous phantom is a practical tool, which will be employed in future, works to optimize veterinary X-ray procedures.

Keywords: radiation protection, phantom, veterinary radiology, computed radiography

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Authors: Styliani Soulioti, Helen Fiddler

Abstract:

The aim of this study was to investigate the approaches used by physiotherapists in the education of patients with chronic low back pain (cLBP) and the rationale that underpins their choice of approach. Therapeutic patient education (TPE) is considered to be an important aspect of modern physiotherapy practice, as it helps patients achieve better self-management and a better understanding of their problem. Previous studies have explored this subject, but the reasoning behind the choices physiotherapists make as educators has not been widely explored, thus making it difficult to understand areas that could be addressed in order to improve the application of TPE.A qualitative study design, guided by a constructivist epistemology was used in this research project. Semi-structured interviews were used to collect data from 7 physiotherapists. Inductive coding and thematic analysis were used, which allowed key themes to emerge. Data analysis revealed two overarching themes: 1) patient-centred versus therapist-centred educational approaches, and 2) behaviourist versus constructivist educational approaches. Physiotherapists appear to use a patient-centred-approach when they explore patients’ beliefs about cLBP and treatment expectations. However, treatment planning and goal-setting were guided by a therapist-centred approach, as physiotherapists appear to take on the role of the instructor/expert, whereas patients were viewed as students. Using a constructivist approach, physiotherapists aimed to provide guidance to patients by combining their professional knowledge with the patients’ individual knowledge, to help the patient better understand their problem, reflect upon it and find a possible solution. However, educating patients about scientific facts concerning cLBP followed a behaviourist approach, as an instructor/student relationship was observed and the learning content was predetermined and transmitted in a one-way manner. The results of this study suggest that a lack of consistency appears to exist in the educational approaches used by physiotherapists. Although patient-centeredness and constructivism appear to be the aims set by physiotherapists in order to optimise the education they provide, a student-teacher relationship appears to dominate when it comes to goal-setting and delivering scientific information.

Keywords: chronic low back pain, educational approaches, health education, patient education

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Authors: Raju Singh, Shikha Singh

Abstract:

This article is note for managing Autistic Child during the Corona time line. It becomes very critical for the primary caregiver as corona pandemic poses new challenges and completely variety of threats to line of treatment, growth, socialization, mental health for children with autism spectrum disorder (ASD), and, so for the family of the children. It is a highly distressful situation, where the line of treatment has shrunken, physical contact has reduced and therapies footprints reduced in several parts of the world. As children with ASD already face socialization challenges, isolation rules imposed by individuals (or social groups), government agencies have only made the situation worse for the children with ASD and their family. This note will try to touch the basics on understanding the ASD and related development disorders, challenges, impact, and suggest approaches to deal with such situation. This document also covers data analysis, deep dive into the increasing impact of ASD on children. This document can also act as a baseline for many researchers, psychiatrists, psychologists, therapists to view the problem statement and measure its impact.

Keywords: autism spectrum disorder, mental health, applied behavior therapy, occupational therapy, social anxiety

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Authors: Samane Sharifi Monfared, Lavdie Rada

Abstract:

Nowadays, autonomous vehicles are developing rapidly toward facilitating human car driving. One of the main issues is road lane detection for a suitable guidance direction and car accident prevention. This paper aims to improve and optimize road line detection based on a combination of camera calibration, the Hough transform, and Canny edge detection. The video processing is implemented using the Open CV library with the novelty of having a scale able region masking. The aim of the study is to introduce automatic road lane detection techniques with the user’s minimum manual intervention.

Keywords: hough transform, canny edge detection, optimisation, scaleable masking, camera calibration, improving the quality of image, image processing, video processing

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Authors: Aziz Ikhlef

Abstract:

Most of multi-slices CT scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80kVp and 140kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Jegede Oluseye Oladayo

Abstract:

The study mapped innovation activities in the formal and informal mining sector in Nigeria. Data were collected through primary and secondary sources. Primary data were collected through guided questionnaire administration, guided interviews and personal observation. A purposive sampling method was adopted to select firms that are micro, small and medium enterprises. The study covered 100 (50 in the formal sector and 50 in the informal sector) purposively selected companies in south-western Nigeria. Secondary data were collected from different published sources. Data were analysed using descriptive and inferential statistics. Of the four types of technological innovations sampled, organisational innovation was found to be highest both in the formal (100%) and informal (100%) sectors, followed by process innovation: 60% in the formal sector and 28% in the informal sector, marketing innovation and diffusion based innovation were implemented by 64% and 4% respectively in the formal sector. There were no R&D activities (intramural or extramural) in both sectors, however, innovation activities occur at moderate levels in the formal sector. This is characterised by acquisition of machinery, equipment, hardware (100%), software (56), training (82%) and acquisition of external knowledge (60%) in the formal sector. In the informal sector, innovation activities were characterised by acquisition of external knowledge (100%), training/learning by experience (100%) and acquisition of tools (68%). The impact of innovation on firm’s performance in the formal sector was expressed mainly as increased capacity of production (100%), reduced production cost per unit of labour (88%), compliance with governmental regulatory requirements (72%) and entry on new markets (60%). In the informal sector, the impact of innovation was mainly expressed in improved flexibility of production (70%) and machinery/energy efficiency (70%). The important technological driver of process innovation in the mining sector was acquisition of machinery which accounts for the prevalence of 100% both in the formal and informal sectors. Next to this is training and re-training of technical staff, 74% in both the formal and the informal sector. Other factors influencing organisational innovation are skill of workforce with a prevalence of 80% in both the formal and informal sector. The important technological drivers include educational background of the manager/head of technical department (54%) for organisational innovation and (50%) for process innovation in the formal sector. The study concluded that innovation competence of the firms was mostly organisational changes.

Keywords: innovation prevalence, innovation activities, innovation performance, innovation drivers

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Authors: Salvador Garcia Bernal, Chi Zheng, Keqi Zhang, Lei Mao

Abstract:

Circulating Tumor Cells (CTC) is used to detect tumoral cell metastases using blood samples of patients with cancer (lung, breast, etc.). Using an immunofluorescent method a three channel image (Red, Green, and Blue) are obtained. These set of images usually overpass the 11 x 30 M pixels in size. An aided tool is designed for imaging cell analysis to segmented and identify the tumorous cell based on the three markers signals. Our Method, it is cell-based (area and cell shape) considering each channel information and extracting and making decisions if it is a valid CTC. The system also gives information about number and size of tumor cells found in the sample. We present results in real-life samples achieving acceptable performance in identifying CTCs in short time.

Keywords: Circulating Tumor Cells (CTC), cell analysis, immunofluorescent, medical image analysis

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Authors: Abdelhadi Adam Salih Denei

Abstract:

Silver nanoparticles (AgNPs) have been used in cancer therapy, and the area of nanomedicine has made unheard-of strides in recent years. A thorough summary of the development and assessment of AgNPs for their possible use in the fight against cancer is the goal of this review. Targeted delivery methods have been designed to optimise therapeutic efficacy by using AgNPs' distinct physicochemical features, such as their size, shape, and surface chemistry. Firstly, the study provides an overview of the several synthesis routes—both chemical and green—that are used to create AgNPs. Natural extracts and biomolecules are used in green synthesis techniques, which are becoming more and more popular since they are biocompatible and environmentally benign. It is next described how synthesis factors affect the physicochemical properties of AgNPs, emphasising how crucial it is to modify these parameters for particular therapeutic uses. An extensive analysis is conducted on the anticancer potential of AgNPs, emphasising their capacity to trigger apoptosis, impede angiogenesis, and alter cellular signalling pathways. The analysis also investigates the potential benefits of combining AgNPs with currently used cancer treatment techniques, including radiation and chemotherapy. AgNPs' safety profile for use in clinical settings is clarified by a comprehensive evaluation of their cytotoxicity and biocompatibility.

Keywords: silver nanoparticles, cancer, nanocarrier system, targeted delivery

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Authors: Michael Vieth, Aric Schadler, Hubert Ballard, J. A. Bauer, Pratibha Thakkar

Abstract:

Introduction: Congenital diaphragmatic hernia (CDH) is a condition characterized by the herniation of abdominal contents into the thoracic cavity requiring postnatal surgical repair. Previous literature suggests improved CDH outcomes at high-volume regional referral centers compared to low-volume centers. The purpose of this study was to examine CDH outcomes at Kentucky Children’s Hospital (KCH), a low-volume center, compared to the Congenital Diaphragmatic Hernia Study Group (CDHSG). Methods: A retrospective chart review was performed at KCH from 2007-2019 for neonates with CDH, and then subdivided into two cohorts: those requiring ECMO therapy and those not requiring ECMO therapy. Basic demographic data and measures of mortality and morbidity including ventilator days and length of stay were compared to the CDHSG. Measures of morbidity for the ECMO cohort including duration of ECMO, clinical bleeding, intracranial hemorrhage, sepsis, need for continuous renal replacement therapy (CRRT), need for sildenafil at discharge, timing of surgical repair, and total ventilator days were collected. Statistical analysis was performed using IBM SPSS Statistics version 28. One-sample t-tests and one-sample Wilcoxon Signed Rank test were utilized as appropriate.Results: There were a total of 27 neonatal patients with CDH at KCH from 2007-2019; 9 of the 27 required ECMO therapy. The birth weight and gestational age were similar between KCH and the CDHSG (2.99 kg vs 2.92 kg, p =0.655; 37.0 weeks vs 37.4 weeks, p =0.51). About half of the patients were inborn in both cohorts (52% vs 56%, p =0.676). KCH cohort had significantly more Caucasian patients (96% vs 55%, p=<0.001). Unadjusted mortality was similar in both groups (KCH 70% vs CDHSG 72%, p =0.857). Using ECMO utilization (KCH 78% vs CDHSG 52%, p =0.118) and need for surgical repair (KCH 95% vs CDHSG 85%, p =0.060) as proxy for severity, both groups’ mortality were comparable. No significant difference was noted for pulmonary outcomes such as average ventilator days (KCH 43.2 vs. CDHSG 17.3, p =0.078) and home oxygen dependency (KCH 44% vs. CDHSG 24%, p =0.108). Average length of hospital stay for patients treated at KCH was similar to CDHSG (64.4 vs 49.2, p=1.000). Conclusion: Our study demonstrates that outcome in CDH patients is independent of center’s case volume status. Management of CDH with a standardized approach in a low-volume center can yield similar outcomes. This data supports the treatment of patients with CDH at low-volume centers as opposed to transferring to higher-volume centers.

Keywords: ECMO, case volume, congenital diaphragmatic hernia, congenital diaphragmatic hernia study group, neonate

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Authors: hassan gheisari

Abstract:

Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder, as prepared, is annealed at three different temperatures (900 ºC, 1000 ºC, and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks, and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic, which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic; magnetic materials; sol– gel, silicate calcium

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Authors: Hassan Gheisari

Abstract:

Ferro silicate calcium nano particles are prepared through the sol-gel method using polyvinyl alcohol (PVA) as a chelating agent. The powder as prepared is annealed at three different temperatures (900 ºC, 1000 ºC and 1100 ºC) for 3 h. The XRD patterns of the samples indicate broad peaks and the full width at half maximum decreased with increasing annealing temperature. FTIR spectra of the samples confirm the presence of metal - oxygen complexes within the structure. The average particle size obtained from PSA curve demonstrates ultrafine particles. SEM micrographs indicate the particles synthesized have spherical morphology. The saturation magnetization (Ms) and remnant magnetization (Mr) of the samples show dependence on particle size and crystallinity of the samples. The highest saturation magnetization is achieved for the sample annealed at 1100 ºC having maximum average particle size. The high saturation magnetization of the samples suggests the present method is suitable for obtaining nano particles magnetic ferro bioceramic which is desirable for practical applications such as hyperthermia bone cancer therapy.

Keywords: hyperthermia, bone cancer, bio ceramic, magnetic materials, sol– gel, silicate calcium

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Authors: Alireza Akbari, Gelareh Babaee Khou

Abstract:

Ground Penetrating Radar (GPR) is an important nondestructive remote sensing tool that has been used in both military and civilian fields. Recently, GPR imaging has attracted lots of attention in detection of subsurface shallow small targets such as landmines and unexploded ordnance and also imaging behind the wall for security applications. For the monostatic arrangement in the space-time GPR image, a single point target appears as a hyperbolic curve because of the different trip times of the EM wave when the radar moves along a synthetic aperture and collects reflectivity of the subsurface targets. With this hyperbolic curve, the resolution along the synthetic aperture direction shows undesired low resolution features owing to the tails of hyperbola. However, highly accurate information about the size, electromagnetic (EM) reflectivity, and depth of the buried objects is essential in most GPR applications. Therefore hyperbolic curve behavior in the space-time GPR image is often willing to be transformed to a focused pattern showing the object's true location and size together with its EM scattering. The common goal in a typical GPR image is to display the information of the spatial location and the reflectivity of an underground object. Therefore, the main challenge of GPR imaging technique is to devise an image reconstruction algorithm that provides high resolution and good suppression of strong artifacts and noise. In this paper, at first, the standard back-projection (BP) algorithm that was adapted to GPR imaging applications used for the image reconstruction. The standard BP algorithm was limited with against strong noise and a lot of artifacts, which have adverse effects on the following work like detection targets. Thus, an improved BP is based on cross-correlation between the receiving signals proposed for decreasing noises and suppression artifacts. To improve the quality of the results of proposed BP imaging algorithm, a weight factor was designed for each point in region imaging. Compared to a standard BP algorithm scheme, the improved algorithm produces images of higher quality and resolution. This proposed improved BP algorithm was applied on the simulation and the real GPR data and the results showed that the proposed improved BP imaging algorithm has a superior suppression artifacts and produces images with high quality and resolution. In order to quantitatively describe the imaging results on the effect of artifact suppression, focusing parameter was evaluated.

Keywords: algorithm, back-projection, GPR, remote sensing

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Authors: Nagwa E. Abd Elazim, Maha S. El-naggar, Rania H. Mohamed, Sara M. Awad

Abstract:

Background: Radiodermatitis is a common side effect of radiation therapy for breast cancer. However, there is no current consensus about effective standard therapy for the prevention and management of radiation dermatitis. Topical ectoine has demonstrated efficacy in the treatment of atopic dermatitis owing to its anti-inflammatory activity. Objective: To evaluate the efficacy of topical ectoine in comparison to traditional topical dexpanthenol treatment in the management of acute radiodermatitis in breast cancer patients undergoing adjuvant radiotherapy. Methods: Fifty patients were randomized to use either dexpanthenol 0.5% cream (25 patients), or ectoin 7% cream (25 patients), applied twice daily to the irradiated area during the radiation period and continued for 2 weeks after cessation of radiotherapy. Assessment of radiation skin toxicity using Common Terminology Criteria of Adverse Events (CTCAE) v4.0, radiation-associated symptoms, and adverse events were undertaken weekly during radiotherapy and 2 weeks after the end of radiotherapy. Results: Topical ectoine showed some clinical benefit over dexpanthenol, as shown by delayed time to onset (at week 3 versus week 2, respectively) and larger number of patients who reached grade 0 at the end of treatment (64% vs. 48%, respectively). The clinical symptoms of pain (p = 0.003) and itching (p = 0.001) attributable to radiation were less pronounced with ectoine than with dexpanthenol. Burning and hyperpigmentation were the most common side effects with ectoine. However, no significant difference between dexpanthenol and ectoine treatments was found in any of the side effects (p = 0.1). Conclusion: Ectoin was overall more effective in improving radiation dermatitis than topical dexpanthenol in breast cancer patients. Ectoin could be proposed as a preventive or curative treatment for patients undergoing postoperative irradiation for breast cancer. Further clinical studies with a larger number of patients are recommended for the confirmation of these preliminary results.

Keywords: breast cancer, dexapanthenol, ectoin, radiation dermatitis

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Authors: Amina Aquil, Abdeljalil El Got

Abstract:

Background: Sleep quality is one of the most important indicators related to the quality of life of patients suffering from cancer. Many factors could affect this quality of sleep and then be considered as associated predictors. Methods: The aim of this study was to assess the prevalence of sleep disorders and the associated factors with impaired sleep quality in Moroccan women with gynecological cancer. A cross-sectional study was carried out within the oncology department of the Ibn Rochd University Hospital, Casablanca, on Moroccan women who had undergone radical surgery for gynecological cancer (n=100). Translated and validated Arabic versions of the following international scales were used: Pittsburgh sleep quality index (PSQI), Hospital Anxiety and Depression Scale (HADS), Rosenberg's self-esteem scale (RSES), and Body image scale (BIS). Results: 78% of participants were considered poor sleepers. Most of the patients exhibited very poor subjective quality, low sleep latency, a short period of sleep, and a low rate of usual sleep efficiency. The vast majority of these patients were in poor shape during the day and did not use sleep medication. Waking up in the middle of the night or early in the morning and getting up to use the bathroom were the main reasons for poor sleep quality. PSQI scores were positively correlated with anxiety, depression, body image dissatisfaction, and lower self-esteem (p < 0.001). Conclusion: Sleep quality and its predictors require a systematic evaluation and adequate management to prevent sleep disturbances and mental distress as well as to improve the quality of life of these patients.

Keywords: body image, gynecological cancer, self esteem, sleep quality

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Authors: Ebenezer Obaloluwa Olaniyi

Abstract:

In this paper, an intelligent system has been designed to grade apple based on either its defective or healthy for production in food processing. This paper is segmented into two different phase. In the first phase, the image processing techniques were employed to extract the necessary features required in the apple. These techniques include grayscale conversion, segmentation where a threshold value is chosen to separate the foreground of the images from the background. Then edge detection was also employed to bring out the features in the images. These extracted features were then fed into the neural network in the second phase of the paper. The second phase is a classification phase where neural network employed to classify the defective apple from the healthy apple. In this phase, the network was trained with back propagation and tested with feed forward network. The recognition rate obtained from our system shows that our system is more accurate and faster as compared with previous work.

Keywords: image processing, neural network, apple, intelligent system

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Authors: Abobaker Mohammed Qasem Farhan, Shangming Yang, Mohammed Al-Nehari

Abstract:

Pneumonia is a kind of lung disease that creates congestion in the chest. Such pneumonic conditions lead to loss of life of the severity of high congestion. Pneumonic lung disease is caused by viral pneumonia, bacterial pneumonia, or Covidi-19 induced pneumonia. The early prediction and classification of such lung diseases help to reduce the mortality rate. We propose the automatic Computer-Aided Diagnosis (CAD) system in this paper using the deep learning approach. The proposed CAD system takes input from raw computerized tomography (CT) scans of the patient's chest and automatically predicts disease classification. We designed the Hybrid Deep Learning Algorithm (HDLA) to improve accuracy and reduce processing requirements. The raw CT scans have pre-processed first to enhance their quality for further analysis. We then applied a hybrid model that consists of automatic feature extraction and classification. We propose the robust 2D Convolutional Neural Network (CNN) model to extract the automatic features from the pre-processed CT image. This CNN model assures feature learning with extremely effective 1D feature extraction for each input CT image. The outcome of the 2D CNN model is then normalized using the Min-Max technique. The second step of the proposed hybrid model is related to training and classification using different classifiers. The simulation outcomes using the publically available dataset prove the robustness and efficiency of the proposed model compared to state-of-art algorithms.

Keywords: CT scan, Covid-19, deep learning, image processing, lung disease classification

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Authors: Aziz Ikhlef

Abstract:

Most of multi-slices Computed Tomography (CT) scanners are built with detectors composed of scintillator - photodiodes arrays. The photodiodes arrays are mainly based on front-illuminated technology for detectors under 64 slices and on back-illuminated photodiode for systems of 64 slices or more. The designs based on back-illuminated photodiodes were being investigated for CT machines to overcome the challenge of the higher number of runs and connection required in front-illuminated diodes. In backlit diodes, the electronic noise has already been improved because of the reduction of the load capacitance due to the routing reduction. This is translated by a better image quality in low signal application, improving low dose imaging in large patient population. With the fast development of multi-detector-rows CT (MDCT) scanners and the increasing number of examinations, the clinical community has raised significant concerns on radiation dose received by the patient in both medical and regulatory community. In order to reduce individual exposure and in response to the recommendations of the International Commission on Radiological Protection (ICRP) which suggests that all exposures should be kept as low as reasonably achievable (ALARA), every manufacturer is trying to implement strategies and solutions to optimize dose efficiency and image quality based on x-ray emission and scanning parameters. The added demands on the CT detector performance also comes from the increased utilization of spectral CT or dual-energy CT in which projection data of two different tube potentials are collected. One of the approaches utilizes a technology called fast-kVp switching in which the tube voltage is switched between 80 kVp and 140 kVp in fraction of a millisecond. To reduce the cross-contamination of signals, the scintillator based detector temporal response has to be extremely fast to minimize the residual signal from previous samples. In addition, this paper will present an overview of detector technologies and image chain improvement which have been investigated in the last few years to improve the signal-noise ratio and the dose efficiency CT scanners in regular examinations and in energy discrimination techniques. Several parameters of the image chain in general and in the detector technology contribute in the optimization of the final image quality. We will go through the properties of the post-patient collimation to improve the scatter-to-primary ratio, the scintillator material properties such as light output, afterglow, primary speed, crosstalk to improve the spectral imaging, the photodiode design characteristics and the data acquisition system (DAS) to optimize for crosstalk, noise and temporal/spatial resolution.

Keywords: computed tomography, X-ray detector, medical imaging, image quality, artifacts

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Authors: Jianhong Xiang, Rui Sun, Linyu Wang

Abstract:

In recent years, due to the continuous improvement of deep learning theory, Convolutional Neural Network (CNN) has played a great superior performance in the research of Hyperspectral Image (HSI) classification. Since HSI has rich spatial-spectral information, only utilizing a single dimensional or single size convolutional kernel will limit the detailed feature information received by CNN, which limits the classification accuracy of HSI. In this paper, we design a multi-scale CNN with MLP based on residual and attention modules (INRAM-3DCNN) for the HSI classification task. We propose to use multiple 3D convolutional kernels to extract the packet feature information and fully learn the spatial-spectral features of HSI while designing residual 3D convolutional branches to avoid the decline of classification accuracy due to network degradation. Secondly, we also design the 2D Inception module with a joint channel attention mechanism to quickly extract key spatial feature information at different scales of HSI and reduce the complexity of the 3D model. Due to the high parallel processing capability and nonlinear global action of the Multilayer Perceptron (MLP), we use it in combination with the previous CNN structure for the final classification process. The experimental results on two HSI datasets show that the proposed INRAM-3DCNN method has superior classification performance and can perform the classification task excellently.

Keywords: INRAM-3DCNN, residual, channel attention, hyperspectral image classification

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Authors: Chairun Wiedyaningsih, Sri Suryawati, Yati Soenarto, Muhammad Hakimi

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Background: Many drugs used in paediatrics are not commercially available in suitable dosage forms. Therefore, the drugs often prescribed in extemporaneous compounding dosage form. Compounding can pose health risks include poor quality and unsafe products. Studies of compounding dosage form have primarily focused on prescription profiles, reasons of prescribing never be explored. Objectives: The study was conducted to identify factors influencing physicians’ decision to prescribe extemporaneous compounding dosage form for paediatric outpatients. Setting: Daerah Istimewa Yogyakarta (DIY) province, Indonesia. Method: Qualitative semi-structured interviews were conducted with 15 general physicians and 7 paediatricians to identify the reason of prescribing extemporaneous compounding dosage form. The interviews were transcribed and analysed using thematic analysis. Results: Factors underlying prescribing of compounding could be categorized to therapy, healthcare system, patient and past experience. The primary reasons of therapy factors were limited availability of drug compositions, dosages or formulas specific for children. Beliefs in efficacy of the compounding forms were higher when the drugs used primarily to overcome complex cases. Physicians did not concern about compounding form containing several active substances because manufactured syrups may also contain several active substances. Although medicines were available in manufactured syrups, limited institutional budget was healthcare system factor of compounding prescribing. The prescribing factors related to patients include easy to use, efficient and lower price. The prescribing factors related to past experience were physicians’ beliefs to the progress of patient's health status. Conclusions: Compounding was prescribed based on therapy-related factors, healthcare system factors, patient factors and past experience.

Keywords: compounding dosage form, interview, physician, prescription

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Authors: Carlos M. Goncalves, Luisa Duarte, Teresa Cartaxo

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The aim of this work was to understand the reasons behind the underutilization of electroconvulsive therapy (ECT) in the younger population and raise possible solutions. We conducted a non-systematic review of literature throughout a search on PubMed, using the terms ‘children’, ‘adolescents’ and ‘electroconvulsive’, ‘therapy’. Candidate articles written in languages other than English were excluded. Articles were selected according to title and/or abstract’s content relevance, resulting in a total of 5 articles. ECT is a recognized effective treatment in adults for several psychiatric conditions. As in adults, ECT in children and adolescents is proven most beneficial in the treatment of severe mood disorders, catatonia, and, to a lesser extent, schizophrenia. ECT in adults has also been used to treat autism’s self-injurious behaviours, Tourette’s syndrome and resistant first-episode schizophrenia disorder. Despite growing evidence on its safety and effectiveness in children and adolescents, like those found in adults, ECT remains a controversial and underused treatment in patients this age, even when it is clearly indicated. There are various possible reasons to this; limited awareness among professionals (lack of knowledge and experience among child psychiatrists), stigmatic public opinion (despite positive feedback from patients and families, there is an unfavourable and inaccurate representation in the media, contributing to a negative public opinion), legal restrictions and ethical controversies (restrictive regulations such as a minimum age for administration), lack of randomized trials (the currently available studies are retrospective, with small size samples, and most of the publications are either case reports or case series). This shows the need to raise awareness and knowledge, not only for mental health professionals, but also to the general population, through the media, regarding indications, methods and safety of ECT in order to provide reliable information to the patient and families. Large-scale longitudinal studies are also useful to further demonstrate the efficacy and safety of ECT and can aid in the formulation of algorithms and guidelines as without these changes, the availability of ECT to the younger population will remain restricted by regulations and social stigma. In conclusion, these results highlight that lack of adequate knowledge and accurate information are the most important factors behind the underutilization of ECT in younger population. Mental healthcare professionals occupy a cornerstone position; if data is given by a well-informed healthcare professional instead of the media, general population (including patients and their families) will probably regard the procedure in a more favourable way. So, the starting point should be to improve health care professional’s knowledge and experience on this choice of treatment.

Keywords: adolescents, children, electroconvulsive, therapy

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Authors: R. Rama Kishore, Sunesh

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Nowadays, robust and secure watermarking algorithm and its optimization have been need of the hour. A watermarking algorithm is presented to achieve the copy right protection of the owner based on visual cryptography, histogram shape property and entropy. In this, both host image and watermark are preprocessed. Host image is preprocessed by using Butterworth filter, and watermark is with visual cryptography. Applying visual cryptography on water mark generates two shares. One share is used for embedding the watermark, and the other one is used for solving any dispute with the aid of trusted authority. Usage of histogram shape makes the process more robust against geometric and signal processing attacks. The combination of visual cryptography, Butterworth filter, histogram, and entropy can make the algorithm more robust, imperceptible, and copy right protection of the owner.

Keywords: digital watermarking, visual cryptography, histogram, butter worth filter

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Authors: Soumya Sajjan

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Liver cancer is the most common cancer disease worldwide in men and women, and is one of the few cancers still on the rise. Liver disease is the 4th leading cause of death. According to new NHS (National Health Service) figures, deaths from liver diseases have reached record levels, rising by 25% in less than a decade; heavy drinking, obesity, and hepatitis are believed to be behind the rise. In this study, we focus on Development of Diagnostic Classifier for Ultrasound liver lesion. Ultrasound (US) Sonography is an easy-to-use and widely popular imaging modality because of its ability to visualize many human soft tissues/organs without any harmful effect. This paper will provide an overview of underlying concepts, along with algorithms for processing of liver ultrasound images Naturaly, Ultrasound liver lesion images are having more spackle noise. Developing classifier for ultrasound liver lesion image is a challenging task. We approach fully automatic machine learning system for developing this classifier. First, we segment the liver image by calculating the textural features from co-occurrence matrix and run length method. For classification, Support Vector Machine is used based on the risk bounds of statistical learning theory. The textural features for different features methods are given as input to the SVM individually. Performance analysis train and test datasets carried out separately using SVM Model. Whenever an ultrasonic liver lesion image is given to the SVM classifier system, the features are calculated, classified, as normal and diseased liver lesion. We hope the result will be helpful to the physician to identify the liver cancer in non-invasive method.

Keywords: segmentation, Support Vector Machine, ultrasound liver lesion, co-occurance Matrix

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Authors: Rios A. S., Hild F., Deus E. P., Aimedieu P., Benallal A.

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The damage micromechanisms of chopped strand mats manufactured by compression of Brazilian coconut fiber and coconut fibers in different external conditions (chemical treatment) were used in this study. Mechanical analysis testing uniaxial traction were used with Digital Image Correlation (DIC). The images captured during the tensile test in the coconut fibers and coconut fiber mats showed an uncertainty of measurement in order centipixels. The initial modulus (modulus of elasticity) and tensile strength decreased with increasing diameter for the four conditions of coconut fibers. The DIC showed heterogeneous deformation fields for coconut fibers and mats and the displacement fields showed the rupture process of coconut fiber. The determination of poisson’s ratio of the mat was performed through of transverse and longitudinal deformations found in the elastic region.

Keywords: coconut fiber, mechanical behavior, digital image correlation, micromechanism

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Authors: Luke Sniewski, Pante Farvid, Phil Carter, Rita Csako

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Background and Aims: Self-Perceived Problematic Porn Use (SPPPU) refers to individuals who identify as or perceive themselves to be addicted to porn. These individuals feel they are unable to regulate their porn consumption and experience adverse consequences as a result of their use in everyday life. To the author’s best knowledge, this research represents the first study to intervene with pornography use with mindfulness meditation, and aims to investigate the experiences and challenges of men with SPPPU as they engage in a mindfulness meditation intervention. As meditation is commonly characterized by sitting and observing one’s internal experience with non-reaction and acceptance, the study’s principal hypothesis was that consistent practice of meditation would develop the participant’s capacity to respond to cravings, urges, and unwanted thoughts in less reactive, more productive ways. Method: This 12-mixed method research utilised Single Case Experimental Design (SCED) methodology, with a standard AB design. Each participant was randomly assigned to an initial baseline time period between 2 to 5 weeks before learning the meditation technique and practicing it for the remainder of the 12-week study. The pilot study included 3 participants, while the intervention study included 12. The meditation technique used for the study involved a 15-minute guided breathing exercise in the morning, along with a 15-minute guided concentration meditation in the evening. Results: At the time of submission, only pilot study results were available. Results from the pilot study indicate an improved capacity for self-awareness of the uncomfortable mental and emotional states that drove their participants’ pornography use. Statistically significant reductions were also observed in daily porn use, total weekly time spent viewing porn, as well as lowered Pornography Craving Questionnaire (PCQ) and Problematic Pornography Use Scale (PPUS) scores. Conclusion: Pilot study results suggest that meditation could serve as a complementary tool for health professionals to provide clients in conjunction with therapeutic interventions. Study limitations, directions for future research, and clinical implications to be discussed as well.

Keywords: meditation, behavioural change, pornography, mindfulness

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Authors: Nougrara Zineb

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The unique structure of the blood vessels in the retina has been used for biometric identification. The retina blood vessel pattern is a unique pattern in each individual and it is almost impossible to forge that pattern in a false individual. The retina biometrics’ advantages include high distinctiveness, universality, and stability overtime of the blood vessel pattern. Once the creases have been extracted from the images, a registration stage is necessary, since the position of the retinal vessel structure could change between acquisitions due to the movements of the eye. Image registration consists of following steps: Feature detection, feature matching, transform model estimation and image resembling and transformation. In this paper, we present an algorithm of registration; it is based on the characterization of retinal feature points. For experiments, retinal images from the DRIVE database have been tested. The proposed methodology achieves good results for registration in general.

Keywords: fovea, optic disc, registration, retinal images

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Authors: Berkan Ural, Arif Eser, Sinan Apaydin

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Medical image processing is generally become a challenging task nowadays. Indeed, processing of brain MRI images is one of the difficult parts of this area. This study proposes a hybrid well-defined approach which is consisted from tumor detection, extraction and analyzing steps. This approach is mainly consisted from a computer aided diagnostics system for identifying and detecting the tumor formation in any region of the brain and this system is commonly used for early prediction of brain tumor using advanced image processing and probabilistic neural network methods, respectively. For this approach, generally, some advanced noise removal functions, image processing methods such as automatic segmentation and morphological operations are used to detect the brain tumor boundaries and to obtain the important feature parameters of the tumor region. All stages of the approach are done specifically with using MATLAB software. Generally, for this approach, firstly tumor is successfully detected and the tumor area is contoured with a specific colored circle by the computer aided diagnostics program. Then, the tumor is segmented and some morphological processes are achieved to increase the visibility of the tumor area. Moreover, while this process continues, the tumor area and important shape based features are also calculated. Finally, with using the probabilistic neural network method and with using some advanced classification steps, tumor area and the type of the tumor are clearly obtained. Also, the future aim of this study is to detect the severity of lesions through classes of brain tumor which is achieved through advanced multi classification and neural network stages and creating a user friendly environment using GUI in MATLAB. In the experimental part of the study, generally, 100 images are used to train the diagnostics system and 100 out of sample images are also used to test and to check the whole results. The preliminary results demonstrate the high classification accuracy for the neural network structure. Finally, according to the results, this situation also motivates us to extend this framework to detect and localize the tumors in the other organs.

Keywords: image processing algorithms, magnetic resonance imaging, neural network, pattern recognition

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Authors: Yasser Y. Lenis, Amy Jo Montgomery, Diego F. Carrillo-Gonzalez

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Introduction: The use of didactic instruments in different learning environments plays a pivotal role in enhancing the level of knowledge in veterinary science students. The direct instruction of basic animal reproduction concepts in students enrolled in veterinary medicine programs allows them to elucidate the biological and molecular mechanisms that perpetuate the animal species in an ecosystem. Therefore, universities must implement didactic strategies that facilitate the teaching and learning processes for students and, in turn, enrich learning environments. Objective: to evaluate the effect of the use of a didactic textbook on the level of theoretical knowledge in embryo-maternal recognition for veterinary medicine students. Methods: the participants (n=24) were divided into two experimental groups: control (Ctrl) and treatment (Treat). Both groups received 4 hours of theoretical training regarding the basic concepts in bovine embryo-maternal recognition. However, the Treat group was also exposed to a guided lecture and the activity play-to-learn from a cow reproduction didactic textbook. A pre-test and a post-test were applied to assess the prior and subsequent knowledge in the participants. Descriptive statistics were applied to identify the success rates for each of the tests. Afterwards, a repeated measures model was applied where the effect of the intervention was considered. Results: no significant difference (p>0,05) was observed in the number of right answers for groups Ctrl (54,2%±12,7) and Treat (40,8%±16,8) in the pre-test. There was no difference (p>0,05) compering the number of right answers in Ctrl pre-test (54,2%±12,7) and post-test (60,8±18,8). However, the Treat group showed a significant (p>0,05) difference in the number of right answers when comparing pre-test (40,8%±16,8) and post-test (71,7%±14,7). Finally, after the theoretical training and the didactic activity in the Treat group, an increase of 10.9% (p<0,05) in the number of right answers was found when compared with the Ctrl group. Conclusion: the use of didactic tools that include guided lectures and activities like play-to-learn from a didactic textbook enhances the level of knowledge in an animal reproduction course for veterinary medicine students.

Keywords: animal reproduction, pedagogic, level of knowledge, learning environment

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