Search results for: tumor image

Authors: Jigg Pelayo, Ricardo Villar

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Leaning on the development of aerial laser scanning in the Philippine geospatial industry, researches about remote sensing and machine vision technology became a trend. Object detection via template matching is one of its application which characterized to be fast and in real time. The paper purposely attempts to provide application for robust pattern matching algorithm based on the normalized cross correlation (NCC) criterion function subjected in Object-based image analysis (OBIA) utilizing high-resolution aerial imagery and low density LiDAR data. The height information from laser scanning provides effective partitioning order, thus improving the hierarchal class feature pattern which allows to skip unnecessary calculation. Since detection is executed in the object-oriented platform, mathematical morphology and multi-level filter algorithms were established to effectively avoid the influence of noise, small distortion and fluctuating image saturation that affect the rate of recognition of features. Furthermore, the scheme is evaluated to recognized the performance in different situations and inspect the computational complexities of the algorithms. Its effectiveness is demonstrated in areas of Misamis Oriental province, achieving an overall accuracy of 91% above. Also, the garnered results portray the potential and efficiency of the implemented algorithm under different lighting conditions.

Keywords: algorithm, LiDAR, object recognition, OBIA

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Authors: Ines Elouedi, Atef Hammouda

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This paper presents a new fast version of the generalized Multi-Directional Radon Transform method. The new method uses the inverse Fast Fourier Transform to lead to a faster Generalized Radon projections. We prove in this paper that the fast algorithm leads to almost the same results of the eldest one but with a considerable lower time computation cost. The projection end result of the fast method is a parameterized Radon space where a high valued pixel allows the detection of a curve from the original image. The proposed fast inversion algorithm leads to an exact reconstruction of the initial image from the Radon space. We show examples of the impact of this algorithm on the pattern recognition domain.

Keywords: fast generalized multi-directional Radon transform, curve, exact reconstruction, pattern recognition

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Authors: Hasan Frookh Jamal

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This is a case of a 36-year-old Bahraini gentleman diagnosed to have Cushing's Syndrome with a large anterior mediastinal mass. He was sent abroad to the Speciality hospital in Jordan, where he underwent diagnostic video-assisted thoracoscopy, partial thymectomy and pericardial fat excision. Histopathology of the mass was reported to be an Atypical carcinoid tumor with a low Ki67 proliferation index of 5%, the mitotic activity of 4 MF/10HPF and pathological stage classification(pTNM): pT1aN1. MRI of the pituitary gland showed an ill-defined non-enhancing focus of about 3mm on the Rt side of the pituitary on coronal images, with a similar but smaller one on the left side, which could be due to enhancing pattern rather than a real lesion as reported. The patient underwent Ga68 Dotate PET/CT scan post-operatively, which showed multiple somatostatin receptor-positive lesions seen within the tail, body and head of the pancreas and positive somatostatin receptor lymph nodes located between the pancreatic head and IVC. There was no uptake detected at the anterior mediastinum nor at the site of thymic mass resection. There was no evidence of any positive somatostatin uptake at the soft tissue or lymph nodes. The patient underwent IPSS, which proved that the source is, in fact, an ectopic source of ACTH secretion. Unfortunately, the patient's serum cortisol remained elevated after surgery and failed to be suppressed by 1 mg ODST and by 2 days LLDST with a high ACTH value. The patient was started on Osilodrostat for treatment of hypercortisolism for the time being and his future treatment plan with Lutetium-177 Dotate therapy vs. bilateral adrenalectomy is to be considered in an MDT meeting.

Keywords: cushing syndrome, neuroendocrine tumur, carcinoid tumor, Thymoma

Procedia PDF Downloads 79

Authors: Louis Nahimana

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Most maps are in a raster or pdf format and it is not easy to get vector layers of published maps. Faced to the production of geological simplified map of the northern Lake Tanganyika countries without geological information in vector format, I tried a method of obtaining vector layers from raster layers created from geological maps of Rwanda and DR Congo in pdf and jpg format. The procedure was as follows: The original raster maps were georeferenced using ArcGIS10.2. Under Adobe Photoshop, map areas with the same color corresponding to a lithostratigraphic unit were selected all over the map and saved in a specific raster layer. Using the same image processing software Adobe Photoshop, each RGB raster layer was converted in grayscale type and improved before importation in ArcGIS10. After georeferencing, each lithostratigraphic raster layer was transformed into a multitude of polygons with the tool "Raster to Polygon (Conversion)". Thereafter, tool "Aggregate Polygons (Cartography)" allowed obtaining a single polygon layer. Repeating the same steps for each color corresponding to a homogeneous rock unit, it was possible to reconstruct the simplified geological constitution of Rwanda and the Democratic Republic of Congo in vector format. By using the tool «Append (Management)», vector layers obtained were combined with those from Burundi to achieve vector layers of the geology of the « Northern Lake Tanganyika countries ».

Keywords: creating raster layer under image processing software, raster to polygon, aggregate polygons, adobe photoshop

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Authors: Shuo Mu, Guangzhi Jiang, Jinsa Chen

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The analysis of Indel for RNA sequencing of clinical samples is easily affected by sequencing experiment errors and software selection. In order to improve the efficiency and accuracy of analysis, we developed an automatic reporting system for Indel recognition and annotation based on image snapshot of transcriptome reads alignment. This system includes sequence local-assembly and realignment, target point snapshot, and image-based recognition processes. We integrated high-confidence Indel dataset from several known databases as a training set to improve the accuracy of image processing and added a bioinformatical processing module to annotate and filter Indel artifacts. Subsequently, the system will automatically generate data, including data quality levels and images results report. Sanger sequencing verification of the reference Indel mutation of cell line NA12878 showed that the process can achieve 83% sensitivity and 96% specificity. Analysis of the collected clinical samples showed that the interpretation accuracy of the process was equivalent to that of manual inspection, and the processing efficiency showed a significant improvement. This work shows the feasibility of accurate Indel analysis of clinical next-generation sequencing (NGS) transcriptome. This result may be useful for RNA study for clinical samples with microsatellite instability in immunotherapy in the future.

Keywords: automatic reporting, indel, next-generation sequencing, NGS, transcriptome

Procedia PDF Downloads 176

Authors: Sadeem Aljamaan, Reem Hariri, Rahaf Alghamdi, Batool Alotaibi, Batool Alsenan, Lama Althunayyan, Areej Alnemer

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The aim of this study is to correlate between radiological findings and histopathological results in regard to the breast imaging-reporting and data system scores, size of breast masses, molecular subtypes and suspicious radiological features, as well as to assess the concordance rate in histological grade between core biopsy and surgical excision among breast cancer patients, followed by analyzing the change of concordance rate in relation to neoadjuvant chemotherapy in a Saudi population. A retrospective review was conducted over 6-year period (2017-2022) on all breast core biopsies of women preceded by radiological investigation. Chi-squared test (χ2) was performed on qualitative data, the Mann-Whitney test for quantitative non-parametric variables, and the Kappa test for grade agreement. A total of 641 cases were included. Ultrasound, mammography, and magnetic resonance imaging demonstrated diagnostic accuracies of 85%, 77.9% and 86.9%; respectively. magnetic resonance imaging manifested the highest sensitivity (72.2%), and the lowest was for ultrasound (61%). Concordance in tumor size with final excisions was best in magnetic resonance imaging, while mammography demonstrated a higher tendency of overestimation (41.9%), and ultrasound showed the highest underestimation (67.7%). The association between basal-like molecular subtypes and the breast imaging-reporting and data system score 5 classifications was statistically significant only for magnetic resonance imaging (p=0.04). Luminal subtypes demonstrated a significantly higher percentage of speculation in mammography. Breast imaging-reporting and data system score 4 manifested a substantial number of benign pathologies in all the 3 modalities. A fair concordance rate (k= 0.212 & 0.379) was demonstrated between excision and the preceding core biopsy grading with and without neoadjuvant therapy, respectively. The results demonstrated a down-grading in cases post-neoadjuvant therapy. In cases who did not receive neoadjuvant therapy, underestimation of tumor grade in biopsy was evident. In summary, magnetic resonance imaging had the highest sensitivity, specificity, positive predictive value and accuracy of both diagnosis and estimation of tumor size. Mammography demonstrated better sensitivity than ultrasound and had the highest negative predictive value, but ultrasound had better specificity, positive predictive value and accuracy. Therefore, the combination of different modalities is advantageous. The concordance rate of core biopsy grading with excision was not impacted by neoadjuvant therapy.

Keywords: breast cancer, mammography, MRI, neoadjuvant, pathology, US

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Authors: M. R. Akbari, M. Sadeghi, R. Faghihi, M. A. Mosleh-Shirazi, A. R. Khorrami-Moghadam

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Proton radiotherapy (PRT) is becoming an established treatment modality for cancer. The localized tumors, the same as undifferentiated thyroid tumors are insufficiently handled by conventional radiotherapy, while protons would propose the prospect of increasing the tumor dose without exceeding the tolerance of the surrounding healthy tissues. In spite of relatively high advantages in giving localized radiation dose to the tumor region, in proton therapy, secondary neutron production can have significant contribution on integral dose and lessen advantages of this modality contrast to conventional radiotherapy techniques. Furthermore, neutrons have high quality factor, therefore, even a small physical dose can cause considerable biological effects. Measuring of this neutron dose is a very critical step in prediction of secondary cancer incidence. It has been found that FLUKA Monte Carlo code simulations have been used to evaluate dose due to secondaries in proton therapy. In this study, first, by validating simulated proton beam range in water phantom with CSDA range from NIST for the studied proton energy range (34-54 MeV), a proton therapy in thyroid gland cancer was simulated using FLUKA code. Secondary neutron dose equivalent of some organs and tissues after the target volume caused by 34 and 54 MeV proton interactions were calculated in order to evaluate secondary cancer incidence. A multilayer cylindrical neck phantom considering all the layers of neck tissues and a proton beam impinging normally on the phantom were also simulated. Trachea (accompanied by Larynx) had the greatest dose equivalent (1.24×10-1 and 1.45 pSv per primary 34 and 54 MeV protons, respectively) among the simulated tissues after the target volume in the neck region.

Keywords: FLUKA code, neutron dose equivalent, proton therapy, thyroid gland

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Authors: Junjie Fu

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This paper explores the cultural evolution of the "city-mountain" landscape in ancient Chinese cities, tracing its origins in the regional mountain and town division within the national system. It delves into the cultural archetype of "city-mountain" landscape divine imagery and its spatial characteristics, drawing from the spatial conception of mountain worship and divine order in the model of Kunlun and Penglai. Furthermore, it examines the shift from religious to daily life influences, leading to a poetic aesthetic turn in the "city-mountain" landscape. The paper also discusses the organizational structure of the "city-mountain" poetic landscape and its role as a space for enjoyment. By studying the cultural connotations, evolving relationships, and power mechanisms of the "city-mountain" landscape, this research provides theoretical insights for the construction and development of "city-mountain" landscapes and mountain cities.

Keywords: city-mountain landscape, cultural image, divinity, landscape image, poetry

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Authors: Amit Kamra, V. K. Jain, Pragya

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Mammography is widely used technique for breast cancer screening. There are various other techniques for breast cancer screening but mammography is the most reliable and effective technique. The images obtained through mammography are of low contrast which causes problem for the radiologists to interpret. Hence, a high quality image is mandatory for the processing of the image for extracting any kind of information from it. Many contrast enhancement algorithms have been developed over the years. In the present work, an efficient morphology based technique is proposed for contrast enhancement of masses in mammographic images. The proposed method is based on Multiscale Morphology and it takes into consideration the scale of the structuring element. The proposed method is compared with other state-of-the-art techniques. The experimental results show that the proposed method is better both qualitatively and quantitatively than the other standard contrast enhancement techniques.

Keywords: enhancement, mammography, multi-scale, mathematical morphology

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Authors: Jiahe Liu, Hongyang Yu, Miao Luo, Feng Qian

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The widespread application of 3D human body reconstruction spans various fields. Smplify-X, an algorithm reliant on single-image input, employs three distinct body parameter templates, necessitating gender classification of individuals within the input image. Researchers employed a ResNet18 network to train a gender classifier within the Smplify-X framework, setting the threshold at 0.9, designating images falling below this threshold as having neutral gender. This model achieved 62.38% accurate predictions and 7.54% incorrect predictions. Our improvement involved refining the MobileNet network, resulting in a raised threshold of 0.97. Consequently, we attained 78.89% accurate predictions and a mere 0.2% incorrect predictions, markedly enhancing prediction precision and enabling more precise 3D human body reconstruction.

Keywords: SMPLX, mobileNet, gender classification, 3D human reconstruction

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Authors: Aarushi Agarwal, Tara Singh, I.L Singh, Anju Lata Singh, Trayambak Tiwari

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Simple discrimination in near absence of attention has been widely observed. Dual-task studies with natural scenes studies have been claimed as being preattentive in nature that facilitated categorization simultaneously with the attentional demanding task. So in this study, multiple images at the periphery are presented, initiating parallel processing in near absence of attention. For the central demanding task rotated letters were presented in both conditions, while in periphery natural and animal images were presented. To understand the breakpoint of ability to perform in near absence of attention one, two and three peripheral images were presented simultaneously with central task and subjects had to respond when all belong to the same category. Individual participant performance did not show a significant difference in both conditions central and peripheral task when the single peripheral image was shown. In case of two images high-level parallel processing could take place with little attentional resources. The eye tracking results supports the evidence as no major saccade was made in a large number of trials. Three image presentations proved to be a breaking point of the capacities to perform outside attentional assistance as participants showed a confused eye gaze pattern which failed to make the natural and animal image discriminations. Thus, we can conclude attention and awareness being independent mechanisms having limited capacities.

Keywords: attention, dual task pardigm, parallel processing, break point, saccade

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Authors: Rawan Al-Nemari, Abdulrahman Al-Senaidy, Abdelhabib Semlali

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Background and objectives: The most common cause of death in women worldwide is breast cancer. Regarding all chemotherapy disadvantages and side effects, it’s becoming necessary to identify natural products that target cancer cells with lesser harmful side effects on non-targeted cells and biological environment. Different parts of A. squamosa L., commonly known as custard apple, show varied therapeutic effects. The objective of this study is to investigate in vitro and in vivo, the anti-cancer activity of A. squamosa leaves extract. Methods: The physiological responses using MTT, nucleus staining, and LDH assays were used to evaluate cell survival and proliferation in both ER+ and ER- cells when they were exposed to extract. Monolayer wound repair assay was used to investigate the effect of extracts on cell migration. Apoptotic gene’s expression was investigated by real-time polymerase chain reaction. To study the effect of the extract on the size of tumor, breast cancer induced rats were used. Results: A. squamosa leaves extract showed high anti-proliferative and cytotoxicity effects against different breast cancer cell lines with high concentration, 100 ug/ml. The extracts have reduced the cells wound closure. Polymerase chain reaction revealed downregulation of Bcl-2 and upregulation of Bax. In breast cancer model animal developed in our laboratory, after 4 weeks treatment, treated groups have shown smaller tumor size in comparison with control group (n=4). Conclusion: These results suggest that A. squamosa leaves extract has anti-cancer activity against breast cancer in both in vitro and in vivo, and it may be developed as a potential novel agent to treat breast cancer.

Keywords: apoptosis, breast cancer, migration, proliferation

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Authors: Abder-Rahman Ali, Adélaïde Albouy-Kissi, Manuel Grand-Brochier, Viviane Ladan-Marcus, Christine Hoeffl, Claude Marcus, Antoine Vacavant, Jean-Yves Boire

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In this paper, we present a new segmentation approach for focal liver lesions in contrast enhanced ultrasound imaging. This approach, based on a two-cluster Fuzzy C-Means methodology, considers type-II fuzzy sets to handle uncertainty due to the image modality (presence of speckle noise, low contrast, etc.), and to calculate the optimum inter-cluster threshold. Fine boundaries are detected by a local recursive merging of ambiguous pixels. The method has been tested on a representative database. Compared to both Otsu and type-I Fuzzy C-Means techniques, the proposed method significantly reduces the segmentation errors.

Keywords: defuzzification, fuzzy clustering, image segmentation, type-II fuzzy sets

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Authors: Hyoseong Lee, Duk-jin Kim, Jaehong Oh, Jungil Shin

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Tidal flat in Korean peninsula is one of the largest biodiversity tidal flats in the world. Therefore, digital elevation models (DEM) is continuously demanded to monitor of the tidal flat. In this study, DEM of tidal flat, according to different times, was produced by means of the Drone and commercial software in order to measure seawater change during high tide at water-channel in tidal flat. To correct the produced DEMs of the tidal flat where is inaccessible to collect control points, the DEM matching method was applied by using the reference DEM instead of the survey. After the ortho-image was made from the corrected DEM, the land cover classified image was produced. The changes of seawater amount according to the times were analyzed by using the classified images and DEMs. As a result, it was confirmed that the amount of water rapidly increased as the time passed during high tide.

Keywords: tidal flat, drone, DEM, seawater change

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Authors: Daniel Alvarado Valencia

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Nowadays, the market offers us solutions for everything, creating the idea of an immediate availability of anything we could desire, and the Internet is the mean through which to obtain all this. The proposal of this conference is that this logic puts the subjects in a situation of self-exploitation, and considers the psyche as a productive force by configuring affection and desire from a neoliberal value perspective. It uses Tinder, starting from ethnographical data from Mexico City users, as an example for this. Tinder is an application created to get dates, have sexual encounters and find a partner. It works from the creation and management of a digital profile. It is an example of how futuristic and lonely the current era can be since we got used to interact with other people through screens and images. However, at the same time, it provides solutions to loneliness, since technology transgresses, invades and alters social practices in different ways. Tinder fits into this contemporary context, it is a concrete example of the processes of technification in which social bonds develop through certain devices offered by neoliberalism, through consumption, and where the search of love and courtship are possible through images and their consumption.

Keywords: desire, image, merchandise, neoliberalism

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Authors: Mosab Alrashed, Wei Xu, Stephen Abineri, Yifan Zhao, Jörn Mehnen

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Thermographic inspection is a relatively new technique for Non-Destructive Testing (NDT) which has been gathering increasing interest due to its relatively low cost hardware and extremely fast data acquisition properties. This technique is especially promising in the area of rapid automated damage detection and quantification. In collaboration with a major industry partner from the aerospace sector advanced thermography-based NDT software for impact damaged composites is introduced. The software is based on correlation analysis of time-temperature profiles in combination with an image enhancement process. The prototype software is aiming to a) better visualise the damages in a relatively easy-to-use way and b) automatically and quantitatively measure the properties of the degradation. Knowing that degradation properties play an important role in the identification of degradation types, tests and results on specimens which were artificially damaged have been performed and analyzed.

Keywords: NDT, correlation analysis, image processing, damage, inspection

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Authors: Okhee Woo, Hye Seon Shin

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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

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

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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: Samane Sharifi Monfared, Lavdie Rada

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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

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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: Nasrud Din, Fawad Saeed, Sajid Hussain, Rai Muhammad Dawood Sultan, Premkumar Sellan, Qasim Khan, Wei Lei

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The continuously increasing external quantum efficiencies of Perovskite light-emitting diodes (LEDs) have received significant interest in the scientific community. The need for monitoring and medical diagnostics has experienced a steady growth in recent years, primarily caused by older people and an increasing number of heart attacks, tumors, and cancer disorders among patients. The application of Perovskite near-infrared light-emitting diode (PeNIRLEDs) has exhibited considerable efficacy in bioimaging, particularly in the visualization and examination of blood arteries, blood clots, and tumors. PeNIRLEDs exhibit exciting potential in the field of blood vessel imaging because of their advantageous attributes, including improved depth penetration and less scattering in comparison to visible light. In this study, we synthesized FAPbI₃ Perovskite doped with different concentrations of 5-Aminovaleric acid (5-AVA) 1-6 mg. The incorporation of 5-AVA as a dopant during the FAPbI₃ Perovskite formation influences the FAPbI3 Perovskite’s structural and optical properties, improving its stability, photoluminescence efficiency, and charge transport characteristics. We found a resulting PL emission peak wavelength of 850 nm and bandwidth of 44 nm, along with a calculated quantum yield of 75%. The incorporation of 5-AVA-modified FAPbI₃ Perovskite into LEDs will show promising results, enhancing device efficiency, color purity, and stability. Making it suitable for various medical applications, including subcutaneous deep vein imaging, blood flow visualization, and tumor illumination.

Keywords: perovskite light-emitting diodes, deep vein imaging, blood flow visualization, tumor illumination

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Authors: Alireza Akbari, Gelareh Babaee Khou

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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: 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: Ghada Esheba, Ebtisam Aljerayan, Afnan Al-Ghamdi, Atheer Alsharif, Hanan alzahrani

Abstract:

Background: Primary ovarian neoplasms comprise a heterogeneous group of tumors of three main subtypes: surface epithelial, germ cell, and sex cord-stromal. The wide morphological variation within and between these groups can result in diagnostic difficulties. Gonadal sex cord-stromal tumors (SCST) represent one of the most heterogeneous categories of human neoplasms, because they may contain various combinations of different gonadal sex cord and stromal element. Aim: The aim of this work is to highlight the clinicopathological characteristics of SCST and to assess the value of alpha-inhibin and calretinin in the distinction between SCST and their mimics. Material and methods: This study was carried out on 100 cases using full tissue sections; 70 cases were SCST and 30 cases were histological mimics of SCST. The cases were studied using immunohistochemically using alpha-inhibin. In addition, an ovarian tissue microarray containing 170 benign and malignant ovarian neoplasms was also studied immunohistochemically for calretinin expression. The ovarian microarray included 14 SCST, 59 ovarian serous borderline tumors, 17 mucinous borderline tumors, 10 mucinous adenocarcinomas, 32 endometrioid adenocarcinomas, 34 clear cell carcinomas, and 4 germ cell tumors. Results: 99% of SCST examined using full tissue sections exhibited positive cytoplasmic staining for inhibin. On the contrary, only 7% of the histological mimics (P value < 0.0001). 86% of SCST in the tissue microarray were positive for calretinin with nuclear and/or cytoplasmic staining compared to only 7% of the other tumor types (P value < 0.0001). Conclusions: SCST have characteristic clinicopathological and immunohistochemical features and their recognition is crucial for proper diagnosis and treatment. Alpha-inhibin and calretinin are of great help in the diagnosis of sex cord-stromal tumors.

Keywords: calretinin, granulosa cell tumor, inhibin, sex cord-stromal tumors

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Authors: R. Rama Kishore, Sunesh

Abstract:

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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