Search results for: ultrasound 3D images

Authors: Ravija Gunawardana, Banuka Athuraliya

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Machine learning has emerged as a powerful tool for disease diagnosis and prediction. The use of machine learning algorithms has the potential to improve the accuracy of disease prediction, thereby enabling medical professionals to provide more effective and personalized treatments. This study focuses on developing a machine-learning model for disease prediction using symptoms and X-ray images. The importance of this study lies in its potential to assist medical professionals in accurately diagnosing diseases, thereby improving patient outcomes. Respiratory diseases are a significant cause of morbidity and mortality worldwide, and chest X-rays are commonly used in the diagnosis of these diseases. However, accurately interpreting X-ray images requires significant expertise and can be time-consuming, making it difficult to diagnose respiratory diseases in a timely manner. By incorporating machine learning algorithms, we can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The study utilized the Mask R-CNN algorithm, which is a state-of-the-art method for object detection and segmentation in images, to process chest X-ray images. The model was trained and tested on a large dataset of patient information, which included both symptom data and X-ray images. The performance of the model was evaluated using a range of metrics, including accuracy, precision, recall, and F1-score. The results showed that the model achieved an accuracy rate of over 90%, indicating that it was able to accurately detect and segment regions of interest in the X-ray images. In addition to X-ray images, the study also incorporated symptoms as input data for disease prediction. The study used three different classifiers, namely Random Forest, K-Nearest Neighbor and Support Vector Machine, to predict diseases based on symptoms. These classifiers were trained and tested using the same dataset of patient information as the X-ray model. The results showed promising accuracy rates for predicting diseases using symptoms, with the ensemble learning techniques significantly improving the accuracy of disease prediction. The study's findings indicate that the use of machine learning algorithms can significantly enhance disease prediction accuracy, ultimately leading to better patient care. The model developed in this study has the potential to assist medical professionals in diagnosing respiratory diseases more accurately and efficiently. However, it is important to note that the accuracy of the model can be affected by several factors, including the quality of the X-ray images, the size of the dataset used for training, and the complexity of the disease being diagnosed. In conclusion, the study demonstrated the potential of machine learning algorithms for disease prediction using symptoms and X-ray images. The use of these algorithms can improve the accuracy of disease diagnosis, ultimately leading to better patient care. Further research is needed to validate the model's accuracy and effectiveness in a clinical setting and to expand its application to other diseases.

Keywords: K-nearest neighbor, mask R-CNN, random forest, support vector machine

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Authors: Johnson C. Y. Pang, Bo Peng, Kara K. L. Reeves, Allan C. L. Fud

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Objective: Dry needling (DN) has long been used as a treatment method for various musculoskeletal pain conditions. However, the evidence level of the studies was low due to the limitations of the methodology. Lack of randomization and inappropriate blinding is potentially the main sources of bias. A method that can differentiate clinical results due to the targeted experimental procedure from its placebo effect is needed to enhance the validity of the trial. Therefore, this study aimed to validate the method as a placebo ultrasound(US)-guided DN for patients with knee osteoarthritis (KOA). Design: This is a randomized controlled trial (RCT). Ninety subjects (25 males and 65 females) aged between 51 and 80 (61.26 ± 5.57) with radiological KOA were recruited and randomly assigned into three groups with a computer program. Group 1 (G1) received real US-guided DN, Group 2 (G2) received placebo US-guided DN, and Group 3 (G3) was the control group. Both G1 and G2 subjects received the same procedure of US-guided DN, except the US monitor was turned off in G2, blinding the G2 subjects to the incorporation of faux US guidance. This arrangement created the placebo effect intended to permit comparison of their results to those who received actual US-guided DN. Outcome measures, including the visual analog scale (VAS) and Knee injury and Osteoarthritis Outcome Score (KOOS) subscales of pain, symptoms, and quality of life (QOL), were analyzed by repeated measures analysis of covariance (ANCOVA) for time effects and group effects. The data regarding the perception of receiving real US-guided DN or placebo US-guided DN were analyzed by the chi-squared test. The missing data were analyzed with the intention-to-treat (ITT) approach if more than 5% of the data were missing. Results: The placebo US-guided DN (G2) subjects had the same perceptions as the use of real US guidance in the advancement of DN (p<0.128). G1 had significantly higher pain reduction (VAS and KOOS-pain) than G2 and G3 at 8 weeks (both p<0.05) only. There was no significant difference between G2 and G3 at 8 weeks (both p>0.05). Conclusion: The method with the US monitor turned off during the application of DN is credible for blinding the participants and allowing researchers to incorporate faux US guidance. The validated placebo US-guided DN technique can aid in investigations of the effects of US-guided DN with short-term effects of pain reduction for patients with KOA. Acknowledgment: This work was supported by the Caritas Institute of Higher Education [grant number IDG200101].

Keywords: ultrasound-guided dry needling, dry needling, knee osteoarthritis, physiotheraphy

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Authors: Abraham Terán Salcedo, Didier Samayoa Ochoa

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This work presents a numerical implementation of a method for estimating the box-counting dimension of self-avoiding curves on a planar space, fractal objects captured on digital images; this method is named fractioning estimator. Classical methods of digital image processing, such as noise filtering, contrast manipulation, and thresholding, among others, are used in order to obtain binary images that are suitable for performing the necessary computations of the fractioning estimator. A user interface is developed for performing the image processing operations and testing the fractioning estimator on different captured images of real-life fractal objects. To analyze the results, the estimations obtained through the fractioning estimator are compared to the results obtained through other methods that are already implemented on different available software for computing and estimating the box-counting dimension.

Keywords: box-counting, digital image processing, fractal dimension, numerical method

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Authors: Shehzad Khan, Jehangir Khan, Shah Babar, Rashid Mahmood, Rizwan Khan, Sanya Hadi

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Ascaris lumbricoides are familiar with the roundworm that causes biliary infections in humans. Nevertheless, ascariasis is primarily found in the jejunum and transferred in numerous body parts with the intake of Ascaris lumbricoides present in food and water. These study methods were implemented at the Saidu Teaching Hospital Radiology Department from December 2021 to January 2023. This study includes the participants suffering from biliary ascariasis admitted or visited Saidu Teaching Hospital in that time frame. Clinical assessment of the participants was done based on the appearance of signs and symptoms present in them. The participant's laboratory test was done to determine the level of basic body parameters. After that ultrasonography was used to diagnose the presence and appearance of worms. Endoscopic retrograde cholangiopancreatography (ERCP) was used to extract worms from biliary channels, and the incidence of post-ERCP biliary ascariasis was accessed with ultrasonography. This study's results show the presence of numerous types of worms in the biliary channels of patients. Also, the level of body parameters, for instance, neutrophil, hemoglobin, and others, were compared at the time of admission and at the time of discharge from the hospital. Furthermore, the incidence of post-ERCP biliary ascariasis was reported as 4% in females, and 1% in males, respectively.

Keywords: Ascaris, biliary, ERCP, ultrasound

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Authors: Khalak Bin Khair, Saqib Jahir, Mohammed Ibrahim, Fahad Bin, Debajyoti Karmaker

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Object detection is a computer technology that deals with searching through digital images and videos for occurrences of semantic elements of a particular class. It is associated with image processing and computer vision. On top of object detection, we detect camouflage objects within an image using Deep Learning techniques. Deep learning may be a subset of machine learning that's essentially a three-layer neural network Over 6500 images that possess camouflage properties are gathered from various internet sources and divided into 4 categories to compare the result. Those images are labeled and then trained and tested using vgg16 architecture on the jupyter notebook using the TensorFlow platform. The architecture is further customized using Transfer Learning. Methods for transferring information from one or more of these source tasks to increase learning in a related target task are created through transfer learning. The purpose of this transfer of learning methodologies is to aid in the evolution of machine learning to the point where it is as efficient as human learning.

Keywords: deep learning, transfer learning, TensorFlow, camouflage, object detection, architecture, accuracy, model, VGG16

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Authors: Ariadna Manresa, Ines Ferrer

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Introduction: Ultrasonic moulding process (USM) is a recent injection technology used to manufacture micro components. It is able to melt small amounts of material so the waste of material is certainly reduced comparing to microinjection molding. This is an important advantage when the materials are expensive like medical biopolymers. Micro-scaled components are involved in a variety of uses, such as biomedical applications. It is required replication fidelity so it is important to stabilize the process and minimize the variability of the responses. The aim of this research is to investigate the influence of the main process parameters on the filling behaviour, the dimensional accuracy and the cavity pressure when a micro-plate is manufactured by biomaterials such as PLA and PCL. Methodology or Experimental Procedure: The specimens are manufactured using a Sonorus 1G Ultrasound Micro Molding Machine. The used geometry is a rectangular micro-plate of 15x5mm and 1mm of thickness. The materials used for the investigation are PLA and PCL due to biocompatible and degradation properties. The experimentation is divided into two phases. Firstly, the influence of process parameters (vibration amplitude, sonotrodo velocity, ultrasound time and compaction force) on filling behavior is analysed, in Phase 1. Next, when filling cavity is assured, the influence of both cooling time and force compaction on the cavity pressure, part temperature and dimensional accuracy is instigated, which is done in Phase. Results and Discussion: Filling behavior depends on sonotrodo velocity and vibration amplitude. When the ultrasonic time is higher, more ultrasonic energy is applied and the polymer temperature increases. Depending on the cooling time, it is possible that when mold is opened, the micro-plate temperature is too warm. Consequently, the polymer relieve its stored internal energy (ultrasonic and thermal) expanding through the easier direction. This fact is reflected on dimensional accuracy, causing micro-plates thicker than the mold. It has also been observed the most important fact that affects cavity pressure is the compaction configuration during the manufacturing cycle. Conclusions: This research demonstrated the influence of process parameters on the final micro-plated manufactured. Future works will be focused in manufacturing other geometries and analysing the mechanical properties of the specimens.

Keywords: biomaterial, biopolymer, micro injection molding, ultrasound

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Authors: Abdelhalim. N. Mohammed, Mohammed. Y. Esmail

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In the course of recent decades, medical imaging has been dominated by the use of costly film media for review and archival of medical investigation, however due to developments in networks technologies and common acceptance of a standard digital imaging and communication in medicine (DICOM) another approach in light of World Wide Web was produced. Web technologies successfully used in telemedicine applications, the combination of web technologies together with DICOM used to design a web-based and open source DICOM viewer. The Web server allowance to inquiry and recovery of images and the images viewed/manipulated inside a Web browser without need for any preinstalling software. The dynamic site page for medical images visualization and processing created by using JavaScript and HTML5 advancements. The XAMPP ‘apache server’ is used to create a local web server for testing and deployment of the dynamic site. The web-based viewer connected to multiples devices through local area network (LAN) to distribute the images inside healthcare facilities. The system offers a few focal points over ordinary picture archiving and communication systems (PACS): easy to introduce, maintain and independently platforms that allow images to display and manipulated efficiently, the system also user-friendly and easy to integrate with an existing system that have already been making use of web technologies. The wavelet-based image compression technique on which 2-D discrete wavelet transform used to decompose the image then wavelet coefficients are transmitted by entropy encoding after threshold to decrease transmission time, stockpiling cost and capacity. The performance of compression was estimated by using images quality metrics such as mean square error ‘MSE’, peak signal to noise ratio ‘PSNR’ and compression ratio ‘CR’ that achieved (83.86%) when ‘coif3’ wavelet filter is used.

Keywords: DICOM, discrete wavelet transform, PACS, HIS, LAN

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Authors: Jyoti Bharti, Navneet Manjhi, M. K.Gupta, Bimi Jain

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A reliable gait features are required to extract the gait sequences from an images. In this paper suggested a simple method for gait identification which is based on moments. Moment values are extracted on different number of frames of gray scale and silhouette images of CASIA database. These moment values are considered as feature values. Fuzzy logic and nearest neighbour classifier are used for classification. Both achieved higher recognition.

Keywords: gait, fuzzy logic, nearest neighbour, recognition rate, moments

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Authors: Mahasa Zahirnia

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The purpose of this paper is to explore new and effective ways of optimizing satellite images using artificial intelligence, and the process of implementing reinforcement learning to enhance the quality of data captured within the image. In our implementation of Bellman's Reinforcement Learning equations, associated state diagrams, and multi-stage image processing, we were able to enhance image quality, detect and define objects. Reinforcement learning is the differentiator in the area of artificial intelligence, and Q-Learning relies on trial and error to achieve its goals. The reward system that is embedded in Q-Learning allows the agent to self-evaluate its performance and decide on the best possible course of action based on the current and future environment. Results show that within a simulated environment, built on the images that are commercially available, the rate of detection was 40-90%. Reinforcement learning through Q-Learning algorithm is not just desired but required design criteria for image optimization and enhancements. The proposed methods presented are a cost effective method of resolving uncertainty of the data because reinforcement learning finds ideal policies to manage the process using a smaller sample of images.

Keywords: Q-learning, image optimization, reinforcement learning, Markov decision process

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Authors: Sudeepti Dayal, Neelesh Gupta

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Image abbreviation is utilized for reducing the size of a file without demeaning the quality of the image to an objectionable level. The depletion in file size permits more images to be deposited in a given number of spaces. It also minimizes the time necessary for images to be transferred. Storage of medical images is a most researched area in the current scenario. To store a medical image, there are two parameters on which the image is divided, regions of interest and non-regions of interest. The best way to store an image is to compress it in such a way that no important information is lost. Compression can be done in two ways, namely lossy, and lossless compression. Under that, several compression algorithms are applied. In the paper, two algorithms are used which are, discrete cosine transform, applied to non-region of interest (lossy), and discrete wavelet transform, applied to regions of interest (lossless). The paper introduces SPIHT (set partitioning hierarchical tree) algorithm which is applied onto the wavelet transform to obtain good compression ratio from which an image can be stored efficiently.

Keywords: Compression ratio, DWT, SPIHT, DCT

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Authors: Anshul, Rajni Kalia, Sachin Kumar

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Introduction: The costoclavicular approach, a modification to the infraclavicular approach, has been described for anesthesia for upper limb surgeries. Material And Methods: In this randomized and single-blind study, fourty patients undergoing emergency/elective upper limb surgery were allocated to two groups. Group C and S received ultrasound-guided Costoclavicular block and Supraclavicular block, respectively, with 20 ml 0.5 % ropivacaine with 8 mg dexamethasone under strict asepsis. The primary outcome assessed was the total duration of sensory and motor block in the postoperative period. Secondary outcomes were to compare the time taken to perform the procedure, block characteristics in terms of onset of motor and sensory blockade, the efficacy of analgesia with respect to the time of administration of the first rescue analgesic dose with both the blocks and note the side effects pertaining to either of the blocks. Results: The mean total duration of sensory and motor blockade was longer in group C vs. group S (p=0.002 and 0.024, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). The mean onset of sensory and motor Blockade Time in group S was more than in group C (p<0.001 and <0.001, respectively). The mean duration to perform a block in group S was more than in group C (p=0.012). Conclusion: The costoclavicular approach is better than supraclavicular in terms of rapid execution, faster onset of sensory-motor blockade, prolonged postoperative analgesia and similar PONV and safety profile.

Keywords: costoclavicular, supraclavicular, ropivacaine, dexamethasone

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Authors: M. Elder, L. Beech, A. Mackie

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Heterotopic pregnancy is an uncommon and potentially life-threatening condition in which there is simultaneous occurrence of intrauterine and ectopic pregnancies. It has an incidence of approximately 1:3900 pregnancies, occurring in only 1:30000 spontaneous pregnancies. This study presents a rare case of spontaneous heterotopic pregnancy in a 34-year-old primiparous woman who was brought in by ambulance to the emergency department following collapse at 20+1 weeks gestation after normal first trimester screening and morphology scan. She was hemodynamically unstable and fetal heart rate was 60bpm. Initial resuscitation included transfusion of 2 units packed red blood cells and 1g intravenous tranexamic acid. Bedside ultrasound revealed evidence of approximately 1000ml clot in the right upper quadrant. She underwent a diagnostic laparoscopy and washout, which proceeded to a midline exploratory laparotomy. This revealed a 2.6L hemoperitoneum and query right ectopic pregnancy with calcified areas and clot, with no other cause of bleeding identified. Right salpingectomy was performed, and pathology later confirmed ectopic pregnancy. The intrauterine pregnancy had no complications, and she delivered a healthy full-term baby. This case demonstrates that ultrasound confirmation of intrauterine pregnancy does not exclude coexisting ectopic pregnancy. Heterotopic pregnancy should be considered in any pregnant woman presenting with abdominal pain or signs of hemorrhagic shock, as prompt diagnosis and treatment is essential to minimize foetal and maternal morbidity and mortality.

Keywords: ectopic pregnancy, hemorrhagic shock, salpingectomy, spontaneous heterotopic pregnancy

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Authors: Chin-Chen Chang, I-Ta Lee, Tsung-Ta Ke, Wen-Kai Tai

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Common methods for resizing image size include scaling and cropping. However, these two approaches have some quality problems for reduced images. In this paper, we propose an image resizing algorithm by separating the main objects and the background. First, we extract two feature maps, namely, an enhanced visual saliency map and an improved gradient map from an input image. After that, we integrate these two feature maps to an importance map. Finally, we generate the target image using the importance map. The proposed approach can obtain desired results for a wide range of images.

Keywords: energy map, visual saliency, gradient map, seam carving

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Authors: S. Haider, B. Bhushan

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Eye Gaze behaviour of individuals with and without intellectual disability are investigated in an eye tracking study in terms of sensitivity to Nonaccidental (NAPs) and Metric (MPs) shape properties. Total fixation time is used as an indirect measure of attention allocation. Studies have found Mean reaction times for non accidental properties (NAPs) to be shorter than for metric (MPs) when the MP and NAP differences were equalized. METHODS: Twenty-five individuals with intellectual disability (mild and moderate level of Mental Retardation) and twenty-seven normal individuals were compared on mean total fixation duration, accuracy level and mean reaction time for mild NAPs, extreme NAPs and metric properties of images. 2D images of cylinders were adapted and made into forced choice match-to-sample tasks. Tobii TX300 Eye Tracker was used to record total fixation duration and data obtained from the Areas of Interest (AOI). Variable trial duration (total reaction time of each participant) and fixed trail duration (data taken at each second from one to fifteen seconds) data were used for analyses. Both groups did not differ in terms of fixation times (fixed as well as variable) across any of the three image manipulations but differed in terms of reaction time and accuracy. Normal individuals had longer reaction time compared to individuals with intellectual disability across all types of images. Both the groups differed significantly on accuracy measure across all image types. Normal individuals performed better across all three types of images. Mild NAPs vs. Metric differences: There was significant difference between mild NAPs and metric properties of images in terms of reaction times. Mild NAPs images had significantly longer reaction time compared to metric for normal individuals but this difference was not found for individuals with intellectual disability. Mild NAPs images had significantly better accuracy level compared to metric for both the groups. In conclusion, type of image manipulations did not result in differences in attention allocation for individuals with and without intellectual disability. Mild Nonaccidental properties facilitate better accuracy level compared to metric in both the groups but this advantage is seen only for normal group in terms of mean reaction time.

Keywords: eye gaze fixations, eye movements, intellectual disability, stimulus properties

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Authors: Suzanne Ahmed

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Nanomotors, also commonly referred to as nanorobotics or nanomachines, have garnered considerable research attention due to their numerous potential applications in biomedicine, including drug delivery and microsurgery. Nanomotors typically consist of inorganic or polymeric particles that are powered to undergo motion. These artificial, man-made nanoscale motors operate in the low Reynolds number regime and typically have no moving parts. Several methods have been developed to actuate the motion of nanomotors including magnetic fields, electrical fields, electromagnetic waves, and chemical fuel. Since their introduction in 2012, ultrasonically powered nanomotors have been explored in biocompatible fluids and even within living cells. Due to the common use of ultrasound within the biomedical community for both imaging and therapeutics, the introduction of ultrasonically propelled nanomotors holds significant potential for biomedical applications. In this work, metallic nanomotors are electrochemically plated within porous anodic alumina templates to have a diameter of 300 nm and a length that is 2-4 µm. Nanomotors are placed within an acoustic chamber capable of producing bulk acoustic waves in the ultrasonic range. The motion of nanomotors within biomimetic confines is explored. The control over nanomotor motion is exerted by virtue of the properties of the acoustic signal within these biomimetic confines to control speed, modes of motion and directionality of motion. To expand the range of control over nanorod motion within biomimetic confines, external forces from biocompatible magnetic fields, are exerted onto the acoustically propelled nanomotors.

Keywords: nanomotors, nanomachines, nanorobots, ultrasound

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Authors: Hanan Bishara

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This study deals with the subject of Popular Arabic Proverbs and the stereotypical roles and images that they create about the woman in general and Arab woman in particular. Popular proverbs in general are considered to be essence of experiences of society and the extract of its collective thought establish wisdom in a distinguished concise tight mold or style that affects the majority of people and keep them alive by virtue of constant use and oral currency through which they are transmitted from one generation to another. Proverbs deal with different aspects and types of people, different social relations, including the society's attitude about the woman. Proverbs about women in the human heritage in general and the Arab heritage in particular are considered of a special characteristics and remarkable in their being dynamic ones that move in all directions of life. Most of them carry the essence of the social issues and are distributed in such a way that they have become part of the private life of the general public. This distribution covers all periods and fields of the woman's life, the social, the economic and psychological ones. The woman occupies a major space in the Popular Proverbs because she is the center of social life inside and outside the house. The woman's statuses and images in the provers are numerous and she is often described in parallel images but each one differs from the other. These images intertwine due to their varieties and multiplicity and ultimately, they constitute a general stereotypical image of the woman, which degrades her status as a woman, a mother and a wife. The study shows how Popular Proverbs in Arabic reflect the Arab woman's position and status in her society.

Keywords: Arab, proverb, popular, society, woman

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Authors: Saeed Pourhassan, Nastaran Maghbouli

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1) Background It has been hypothesized that, in individuals with diabetes mellitus, the peripheral nerve is swollen due to sorbitol over-accumulation. Additionally growing evidence supported electro diagnostic study of diabetes induced neuropathy as a method having some challenges. 2) Objective To examine the performance of sonographic cross-sectional area (CSA) measurements in the diagnosis of diabetic polyneuropathy (DPN). 3) Data Sources Electronic databases, comprising PubMed and EMBASE and Google scholar, were searched for the appropriate studies before Jan 1, 2020. 4) Study Selection Eleven trials comparing different peripheral nerve CSA measurements between participants with and without DPN were included. 5) Data Extraction Study design, participants' demographic characteristics, diagnostic reference of DPN, and evaluated peripheral nerves and methods of CSA measurement. 6) Data Synthesis Among different peripheral nerves, Tibial nerve diagnostic odds ratios pooled from five studies (713 participants) were 4.46 (95% CI, 0.35–8.57) and the largest one with P<0.0001, I²:64%. Median nerve CSA at wrist and mid-arm took second and third place with ORs= 2.82 (1.50-4.15), 2.02(0.26-3.77) respectively. The sensitivities and specificities pooled from two studies for Sural nerve were 0.78 (95% CI, 0.68–0.89), and 0.68 (95% CI, 0.53–0.74). Included studies for other nerves were limited to one study. The largest sensitivity was for Sural nerve and the largest specificity was for Tibial nerve. 7) Conclusions The peripheral nerves CSA measured by ultrasound imaging is useful for the diagnosis of DPN and is most significantly different between patients and participants without DPN at the Tibial nerve. Because the Tibial nerve CSA in healthy participants, at various locations, rarely exceeds 24 mm2, this value can be considered as a cutoff point for diagnosing DPN.

Keywords: diabetes, diagnosis, polyneuropathy, ultrasound

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Authors: Manik Sharma, Ganapathy Krishnamurthi

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The cost of some drugs and medical treatments has risen in recent years, that many patients are having to go without. A classification project could make researchers more efficient. One of the more surprising reasons behind the cost is how long it takes to bring new treatments to market. Despite improvements in technology and science, research and development continues to lag. In fact, finding new treatment takes, on average, more than 10 years and costs hundreds of millions of dollars. If successful, we could dramatically improve the industry's ability to model cellular images according to their relevant biology. In turn, greatly decreasing the cost of treatments and ensure these treatments get to patients faster. This work aims at solving a part of this problem by creating a cellular image classification model which can decipher the genetic perturbations in cell (occurring naturally or artificially). Another interesting question addressed is what makes the deep-learning model decide in a particular fashion, which can further help in demystifying the mechanism of action of certain perturbations and paves a way towards the explainability of the deep-learning model.

Keywords: cellular images, genetic perturbations, deep-learning, explainability

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Authors: Yoganathan Karthik, Guhanathan Poravi

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Colorizing near-infrared (NIR) images poses unique challenges due to the absence of color information and the nuances in light absorption. In this paper, we present an approach to NIR image colorization utilizing a synthetic dataset generated from visible light images. Our method addresses two major challenges encountered in NIR image colorization: accurately colorizing objects with color variations and avoiding over/under saturation in dimly lit scenes. To tackle these challenges, we propose a Generative Adversarial Network (GAN)-based framework that learns to map NIR images to their corresponding colorized versions. The synthetic dataset ensures diverse color representations, enabling the model to effectively handle objects with varying hues and shades. Furthermore, the GAN architecture facilitates the generation of realistic colorizations while preserving the integrity of dimly lit scenes, thus mitigating issues related to over/under saturation. Experimental results on benchmark NIR image datasets demonstrate the efficacy of our approach in producing high-quality colorizations with improved color accuracy and naturalness. Quantitative evaluations and comparative studies validate the superiority of our method over existing techniques, showcasing its robustness and generalization capability across diverse NIR image scenarios. Our research not only contributes to advancing NIR image colorization but also underscores the importance of synthetic datasets and GANs in addressing domain-specific challenges in image processing tasks. The proposed framework holds promise for various applications in remote sensing, medical imaging, and surveillance where accurate color representation of NIR imagery is crucial for analysis and interpretation.

Keywords: computer vision, near-infrared images, automatic image colorization, generative adversarial networks, synthetic data

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Authors: T. R. Sharika, Ashwini Kumar, Kamal Bijlani

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Encryption is the process of converting crucial information’s unreadable to unauthorized persons. Image security is an important type of encryption that secures all type of images from cryptanalysis. A stream cipher is a fast symmetric key algorithm which is used to convert plaintext to cipher text. In this paper we are proposing an image encryption algorithm with Discrete Cosine Transform and Stream Ciphers that can improve compression of images and enhanced security. The paper also explains the use of a shuffling algorithm for enhancing securing.

Keywords: decryption, DCT, encryption, RC4 cipher, stream cipher

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Authors: Belgherbi Aicha, Hadjidj Ismahen, Bessaid Abdelhafid

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Interpretation of medical images benefits from anatomical and physiological priors to optimize computer-aided diagnosis applications. Segmentation of liver, spleen and kidneys is regarded as a major primary step in the computer-aided diagnosis of abdominal organ diseases. In this paper, a semi-automated method for medical image data is presented for the abdominal organ segmentation data using mathematical morphology. Our proposed method is based on hierarchical segmentation and watershed algorithm. In our approach, a powerful technique has been designed to suppress over-segmentation based on mosaic image and on the computation of the watershed transform. Our algorithm is currency in two parts. In the first, we seek to improve the quality of the gradient-mosaic image. In this step, we propose a method for improving the gradient-mosaic image by applying the anisotropic diffusion filter followed by the morphological filters. Thereafter, we proceed to the hierarchical segmentation of the liver, spleen and kidney. To validate the segmentation technique proposed, we have tested it on several images. Our segmentation approach is evaluated by comparing our results with the manual segmentation performed by an expert. The experimental results are described in the last part of this work.

Keywords: anisotropic diffusion filter, CT images, morphological filter, mosaic image, simultaneous organ segmentation, the watershed algorithm

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Authors: Luca Collini, Michele Antolotti, Diego Schiavi

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At present, complex geometries within production time shrinkage, rapidly increasing demand, and high-quality standard requirement make the non-destructive (ND) control of additively manufactured components indispensable means. On the other hand, a technology gap and the lack of standards regulating the methods and the acceptance criteria indicate the NDT of these components a stimulating field to be still fully explored. Up to date, penetrant testing, acoustic wave, tomography, radiography, and semi-automated ultrasound methods have been tested on metal powder based products so far. External defects, distortion, surface porosity, roughness, texture, internal porosity, and inclusions are the typical defects in the focus of testing. Detection of density and layers compactness are also been tried on stainless steels by the ultrasonic scattering method. In this work, the authors want to present and discuss the radiographic and the ultrasound ND testing on additively manufactured Ti₆Al₄V and inconel parts obtained by the selective laser melting (SLM) technology. In order to test the possibilities given by the radiographic method, both X-Rays and γ-Rays are tried on a set of specifically designed specimens realized by the SLM. The specimens contain a family of defectology, which represent the most commonly found, as cracks and lack of fusion. The tests are also applied to real parts of various complexity and thickness. A set of practical indications and of acceptance criteria is finally drawn.

Keywords: non-destructive testing, selective laser melting, radiography, UT method

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Authors: Zeenat Parveen, Ashiq Hussain

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This review paper consists of applications of PDMS (polydimethylsiloxane) materials for enhanced performance, optical fiber sensors in acousto-ultrasonic, mechanical measurements, current applications, sensing, measurements and interferometric optical fiber sensors. We will discuss the basic working principle of fiber optic sensing technology, various types of fiber optic and the PDMS as a coating material to increase the performance. Optical fiber sensing methods for detecting dynamic strain signals, including general sound and acoustic signals, high frequency signals i.e. ultrasonic/ultrasound, and other signals such as acoustic emission and impact induced dynamic strain. Optical fiber sensors have Industrial and civil engineering applications in mechanical measurements. Sometimes it requires different configurations and parameters of sensors. Optical fiber current sensors are based on Faraday Effect due to which we obtain better performance as compared to the conventional current transformer. Recent advancement and cost reduction has simulated interest in optical fiber sensing. Optical techniques are also implemented in material measurement. Fiber optic interferometers are used to sense various physical parameters including temperature, pressure and refractive index. There are four types of interferometers i.e. Fabry–perot, Mach-Zehnder, Michelson, and Sagnac. This paper also describes the future work of fiber optic sensors.

Keywords: fiber optic sensing, PDMS materials, acoustic, ultrasound, current sensor, mechanical measurements

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Authors: Chia-Yen Lee, Hao-Jen Wang, Jhih-Hao Lai

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In recent years, infrared (IR) imaging has been considered as a potential tool to assess the efficacy of chemotherapy and early detection of breast cancer. Regions of tumor growth with high metabolic rate and angiogenesis phenomenon lead to the high temperatures. Observation of differences between the heat maps in long term is useful to help assess the growth of breast cancer cells and detect breast cancer earlier, wherein the multi-time infrared image alignment technology is a necessary step. Representative feature points detection and matching are essential steps toward the good performance of image registration and quantitative analysis. However, there is no clear boundary on the infrared images and the subject's posture are different for each shot. It cannot adhesive markers on a body surface for a very long period, and it is hard to find anatomic fiducial markers on a body surface. In other words, it’s difficult to detect and match features in an IR sequence images. In this study, automated feature detection and matching algorithms with two type of automatic feature points (i.e., vascular branch points and modified Harris corner) are developed respectively. The preliminary results show that the proposed method could identify the representative feature points on the IR breast images successfully of 98% accuracy and the matching results of 93% accuracy.

Keywords: Harris corner, infrared image, feature detection, registration, matching

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Authors: Narupon Kunbootsri, P. Sirasaporn

Abstract:

Frozen shoulder is a common problem present by pain and limit range of motion. The prevalence of frozen shoulder showed 18-31% of population. The effect of frozen shoulder lead to limit activities daily living life, high medical care cost and so on. Physiotherapy is one of the treatments for frozen shoulder but there was no data about the treatment of physiotherapy. Moreover, it is question about onset of symptom relate to physiotherapy program and obtaining physical modalities and delayed start physiotherapy program lead to delayed improvement. Thus the aim of this study was to investigate physiotherapy program for frozen shoulder relate to onset of symptom, range of motion and obtaining physical modalities. A retrospective study design was conducted. 182 medical records of patients with frozen shoulder were reviewed. These frozen shoulders were treated at physiotherapy unit, department of Rehabilitation last 3 years (January, 2014- December, 2016). The data consist of onset of symptom, range of motion and obtaining physical modalities were recorded. There was a statistically significant increase in shoulder flexion [mean difference 38.88 with 95%CI were [16.00-61.77], shoulder abduction [mean difference 48.47 with 95%CI were 16.07-90.59], shoulder internal rotation [mean difference 22.36 with 95%CI were 2.81-37.18] and shoulder external rotation [mean difference 32.12 with 95%CI were [(-2.47)-(46.91)]. In addition, the onset of symptom was 76.42±46.90 days. And the physical modalities used frequently were hot pack 14.8% and ultrasound diathermy 13.7%. In conclusion, the physiotherapy program including, hot pack and ultrasound diathermy seem to be useful for frozen shoulder. But onset of symptom is too long to start physiotherapy programs.

Keywords: frozen shoulder, range of motions, onset of symptom, physiotherapy, physical modality

Procedia PDF Downloads 290

Authors: Varsha Singh, Shraddha Prajapati, M. B. Kiran

Abstract:

Texture identification is useful in predicting the functionality of a component. Many of the existing texture identification methods are of contact in nature, which limits its measuring speed. These contact measurement techniques use a diamond stylus and the diamond stylus being sharp going to damage the surface under inspection and hence these techniques can be used in statistical sampling. Though these contact methods are very accurate, they do not give complete information for full characterization of surface. In this context, the presented method assumes special significance. The method uses a relatively low cost vision system for image acquisition. Software is developed based on wavelet transform, for analyzing texture images. Specimens are made using different manufacturing process (shaping, grinding, milling etc.) During experimentation, the specimens are illuminated using proper lighting and texture images a capture using CCD camera connected to the vision system. The software installed in the vision system processes these images and subsequently identify the texture of manufacturing processes.

Keywords: diamond stylus, manufacturing process, texture identification, vision system

Procedia PDF Downloads 292

Authors: Zainab Elazab, Azhar Aziz

Abstract:

Background: Spontaneous Splenic artery pseudoaneurysm rupture is a rare condition which is potentially life threatening, if not detected and managed early. We report a case of abdominal pain with intraperitoneal free fluid, which turned out to be spontaneous rupture of a splenic artery pseudoaneurysm, and was treated with arterial embolization. Case presentation: A 28-year old, previously healthy male presented to the ED with a history of sudden onset upper abdominal pain and fainting attack. The patient denied any history of trauma or prior similar attacks. On examination, the patient had tachycardia and a low-normal BP (HR 110, BP 106/66) but his other vital signs were normal (Temp. 37.2, RR 18 and SpO2 100%). His abdomen was initially soft with mild tenderness in the upper region. Blood tests showed leukocytosis of 12.3 X109/L, Hb of 12.6 g/dl and lactic acid of 5.9 mmol/L. Ultrasound showed trace of free fluid in the perihepatic and perisplenic areas, and a splenic hypoechoic lesion. The patient remained stable; however, his abdomen became increasingly tender with guarding. We made a provisional diagnosis of a perforated viscus and the patient was started on IV fluids and IV antibiotics. An erect abdominal x-ray did not show any free air under the diaphragm so a CT abdomen was requested. Meanwhile, bedside ultrasound was repeated which showed increased amount of free fluid, suggesting intra-abdominal bleeding as the most probable etiology for the condition. His CT abdomen revealed a splenic injury with multiple lacerations, a focal intrasplenic enhancing area on venous phase scan (suggesting a pseudoaneurysm with associated splenic intraparenchymal, sub capsular and perisplenic hematomas). Free fluid in the subhepatic and intraperitoneal regions along the small bowel was also detected. Angiogram was done which confirmed a diagnosis of pseudoaneurysm of intrasplenic arterial branch, and angio-embolization was done to control the bleeding. The patient was later discharged in good condition with a surgery follow-up. Conclusion: Splenic artery pseudoaneurysm rupture is a rare cause of abdominal pain which should be considered in any case of abdominal pain with intraperitoneal bleeding. Early management is crucial as it carries a high mortality. Bedside ultrasound is a useful tool to help for early diagnosis of such cases.

Keywords: abdominal pain, pseudo aneurysm, rupture, splenic artery

Procedia PDF Downloads 312

Authors: M. Prema Kumar, P. Rajesh Kumar

Abstract:

The increasing interest in image fusion (combining images of two or more modalities such as infrared and visible light radiation) has led to a need for accurate and reliable image assessment methods. This paper gives a novel approach of merging the information content from several videos taken from the same scene in order to rack up a combined video that contains the finest information coming from different source videos. This process is known as video fusion which helps in providing superior quality (The term quality, connote measurement on the particular application.) image than the source images. In this technique different sensors (whose redundant information can be reduced) are used for various cameras that are imperative for capturing the required images and also help in reducing. In this paper Image fusion technique based on multi-resolution singular value decomposition (MSVD) has been used. The image fusion by MSVD is almost similar to that of wavelets. The idea behind MSVD is to replace the FIR filters in wavelet transform with singular value decomposition (SVD). It is computationally very simple and is well suited for real time applications like in remote sensing and in astronomy.

Keywords: multi sensor image fusion, MSVD, image processing, monochrome video

Procedia PDF Downloads 578

Authors: Ibtihal D. Mustafa, Mawia A. Hassan

Abstract:

Tumor segmentation from MRI image is important part of medical images experts. This is particularly a challenging task because of the high assorting appearance of tumor tissue among different patients. MRI images are advance of medical imaging because it is give richer information about human soft tissue. There are different segmentation techniques to detect MRI brain tumor. In this paper, different procedure segmentation methods are used to segment brain tumors and compare the result of segmentations by using correlation and structural similarity index (SSIM) to analysis and see the best technique that could be applied to MRI image.

Keywords: MRI, segmentation, correlation, structural similarity

Procedia PDF Downloads 413

Authors: M. Nadeem, Y. K. Chang, C. Diallo, U. Venkatadri, P. Havard, T. Nguyen-Quang

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Uniform distribution of agro-chemicals is highly important because there is a significant loss of agro-chemicals, for example from pesticide, during spraying due to non-uniformity of droplet and off-target drift. Improving the efficiency of spray pattern for different cropping systems would reduce energy, costs and to minimize environmental pollution. In this paper, we examine the water jet patterns in order to study the performance and uniformity of water distribution during the spraying process. We present a method to quantify the water amount from a sprayer jet by using the Particle Image Velocimetry (PIV) system. The results of the study will be used to optimize sprayer or nozzles design for chemical application. For this study, ten sets of images were acquired by using the following PIV system settings: double frame mode, trigger rate is 4 Hz, and time between pulsed signals is 500 µs. Each set of images contained different numbers of double-framed images: 10, 20, 30, 40, 50, 60, 70, 80, 90 and 100 at eight different pressures 25, 50, 75, 100, 125, 150, 175 and 200 kPa. The PIV images obtained were analysed using custom-made image processing software for droplets and volume calculations. The results showed good agreement of both manual and PIV measurements and suggested that the PIV technique coupled with image processing can be used for a precise quantification of flow through nozzles. The results also revealed that the method of measuring fluid flow through PIV is reliable and accurate for sprayer patterns.

Keywords: image processing, PIV, quantifying the water volume from nozzle, spraying pattern

Procedia PDF Downloads 241