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106 articles for “medical image processing”
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Medical Image Processing Using Data Science: A Review
Abstract: The purpose of this work is to introduce data science in medical imaging. Both theoretical advancements and real-world applications are covered in this research work. The healthcare industry is distinct from all other industries and is a special sector. It is a top-priority industry that consumes a sizable percentage of the federal budget. In general, only doctors can analyses images, but thanks to technology, we are now able to use …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 9, Issue 3, 2022 · pp. 7–15 Read article
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Fusion of CT and MRI Scanned Medical Images Using Image Processing
Abstract: ABSTRACTIn the field of medicine, to evaluate or to examine the inner body parts, different radiometric scanning techniques can be used. Some most commonly used scanning techniques include the computerized tomography (CT) scan and magnetic resonance imaging (MRI) scan but the images of various body parts taken by using these scanning techniques have their own merits and demerits. MRI scans can show the images of soft tissues very clearly but …
Published in Journal of Computer Technology & Applications · Vol. 3, Issue 3, 2012 · pp. 17–20 Read article
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Histogram Equalization for Image Enhancement Using Kidney Ultrasound Images
Abstract: Medical image processing plays an essential role in providing information in wide area for such advanced images. Kidney Ultrasound image (KUI) is an advanced medical imaging technique providing rich information about the size, shape, and location of the kidneys. KUI obtained from Doppler technique colored coded vessels is a valuable tool to help physicians to diagnose and treat various diseases. Ultrasound technology allows quick visualization of the kidneys and related …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 2, 2015 · pp. 20–26 Read article
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CNN-Based Wound Segmentation: A Review of Models and Performance Evaluation
Abstract: Deep learning, particularly convolutional neural networks (CNNs), has altered medical image processing by automating and precisely segmenting complex medical pictures. Wound segmentation, a critical application in automated wound assessment, is essential for wound size estimation, classification, and healing progress monitoring. This study presents a comprehensive review of CNN-based wound segmentation models, focusing on their architectures, methodologies, and performance on diverse datasets. Four deep learning models, including two U-Net variants (5-layer …
Published in Current Trends in Signal Processing · Vol. 15, Issue 1, 2025 · pp. 33–46 Read article
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A Split and Merge UNet: A Deep Learning Assisted UNet Model to Segment Corpus Callosum of Brain for Automatic Autism Detection
Abstract: In recent years, deep learning techniques have shown remarkable performance in various image analysis applications, particularly in the domain of medical image processing. Among these, image segmentation plays a critical role, as it helps in isolating and analyzing specific regions within medical images. The proposed study focuses on segmenting the corpus callosum, a vital structure in the human brain, using a novel optimization technique known as the Split and Merge …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 11, Issue 3, 2024 · pp. 1–9 Read article
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Scaling of Machine Learning Techniques in Medical Imagining and Biomedical Applications Concerning Healthcare
Abstract: Machine learning refers to a field within computer science enabling computers to learn without explicit programming. Stemming from artificial intelligence's study of pattern recognition and computational learning theory, machine learning develops algorithms capable of learning from vast datasets and making predictions. Its applications span diverse computing tasks like email filtering, network intrusion detection, optical character recognition, and computer vision, where conventional algorithm design proves challenging. Notably, in computer vision, a …
Published in Journal of Computer Technology & Applications · Vol. 15, Issue 1, 2024 · pp. 41–44 Read article
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A Meta-Analysis of the Role of Serverless Computing Models in Modern e-Healthcare Systems
Abstract: The integration of serverless computing models in e-healthcare systems represents a paradigm shift in healthcare technology infrastructure. This meta-analysis examines the role, benefits, and challenges of serverless architectures in modern healthcare applications, focusing on studies published between 2019 and 2025. Serverless computing offers unprecedented scalability, cost-efficiency, and operational flexibility, making it particularly suited for healthcare applications handling variable workloads such as medical imaging processing, real-time patient monitoring, and electronic health …
Published in Recent Trends in Parallel Computing · Vol. 12, Issue 3, 2025 · pp. 49–58 Read article
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A Comparison Study of Different Classification Algorithm on Brain Tumor Segmentation
Abstract: A brain tumor is a tissue mass caused by aberrant cell proliferation in the brain. It is a collection of tissues that causes hormonal alterations and eventually death. In order to save human lives, brain tumors prognosis and prevention is a difficult task. The use of modern medical image processing approaches has made the identification of brain tumors more flexible in recent years. Due to the absence of ionizing radiations, …
Published in Trends in Opto-electro & Optical Communication · Vol. 11, Issue 3, 2021 · pp. 1–7 Read article
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A Review on Segmentation Approaches for Brain Tumor Detection
Abstract: It is commonly said statement ‘the health is wealth’, so if you are healthy then everything is with you. Although everyone takes care of their health in their own ways but some diseases are not under the control of the human being.The “tumor” is one of the crucial diseases which is till now, out of control, in which brain tumor is again a serious issue. The most crucial job which …
Published in Research & Reviews: A Journal of Embedded System & Applications · Vol. 9, Issue 1, 2021 · pp. 6–12 Read article
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Q-Metrics for Early Detection of Cervical Cancer
Abstract: The most prevalent form of cancer in women worldwide is uterine cervical cancer. Through screening programs aimed at detecting precancerous lesions most cases of cervical cancer can be prevented. In this article, Q-metrics has been proposed for carrying out automated image segmentation of uterine cervical cancer. The validation of detection of cervical lesions is an important issue in medical image processing because it has a specific impact on surgical planning. …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 1, Issue 1, 2014 · pp. 26–30 Read article
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Ameliorated perceptive approach to MSRCR algorithm for image augmentation
Abstract: Retinex theory was developedby Edwin H.Land in the year of 1964.Retinex based image enhancement system improves the quality of image. The dominant assumption of retinex theory is that the image can be decomposed in to two factors, one is Reflectance and the other one is illumination. It increases the human perception of information. The color image enhancement methods are used to increase the contrast of color images. The human visual …
Published in Journal of Multimedia Technology & Recent Advancements · Vol. 5, Issue 1, 2018 · pp. 17–26 Read article
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Enhancing Radiographic Dental Image Visualisation with Colourisation and Graphical User
Abstract: Radiography has been used in dentistry to find cavities, bone loss, hidden dental structures, tumour, and cysts. Due to the monochromatic characteristic of X-ray images, it is difficult to discern disorders and explain the diagnosis procedure. Enhance the visualization of X-rays is one of the ways to ease the work of the dentist. There were several studies to enhance visualization by giving pseudo colour shades to monochromatic images. The conclusion …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 7, Issue 2, 2020 · pp. 7–19 Read article
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A Novel Approach of Medical Image Fusion using Wavelet Transforms
Abstract: Image processing applications have been growing rapidly in real world. The term fusion means an approach to extract the useful information from several modalities. Image fusion (IF) is used to integrate the complementary information obtained from multisensor, multiview and/or multitemporal and get an image of more information and the quality of which cannot be achieved from any individual image. Different fusion algorithms are useful in many applications like medical diagnosis …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 5, Issue 1, 2018 · pp. 18–25 Read article
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Study on Brain Tumor Detection Using Morphological Operations in MATLAB with Graphical User Interface (GUI)
Abstract: Brain tumor detection plays a crucial role in early diagnosis and effective treatment planning. This research presents a MATLAB-based Graphical User Interface (GUI) for Brain Tumor Detection, incorporating a comprehensive pipeline of image processing techniques. The GUI provides a user-friendly platform, empowering medical professionals to accurately and efficiently analyze MRI brain scans. The GUI begins with text removal to eliminate any textual artifacts that may be present in the MRI …
Published in International Journal of Radio Frequency Innovations · Vol. 1, Issue 1, 2023 · pp. 24–31 Read article
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A Review on Neural Networks and its Applications
Abstract: Neural Networks have been a hotspot domain for researchers due to its increasing area of applications in areas where huge amounts of data is used and the main goal is to infer patterns out of it. This passage offers an assessment of Neural Networks and their pragmatic uses in real-world situations. It provides information regarding the basic structure of Neural Networks and its working principles. There are also brief introductions …
Published in Journal of Computer Technology & Applications · Vol. 14, Issue 2, 2023 · pp. 60–71 Read article
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Data to Diagnosis: A Systematic Review of AI/ML in Healthcare
Abstract: Artificial Intelligence (AI) and Machine Learning (ML) are fast revolutionizing the diagnosis of healthcare by augmenting accuracy, speed, and efficiency. AI/ML technologies facilitate earlier and more accurate disease identification with advanced algorithms for image processing, predictive modelling, and pattern recognition, frequently outperforming conventional diagnostic techniques. This review delves into the key contribution of AI/ML in contemporary healthcare, such as its use in clinical data analysis, imaging reports, and patient histories …
Published in International Journal of Biomedical Innovations and Engineering · Vol. 3, Issue 2, 2025 Read article
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Verilog-Based Image Processing on Field Programmable Gate Arrays: Design and Implementation
Abstract: Integrated circuits known as Field Programmable Gate Arrays (FPGAs) are frequently offered for sale off the shelf. They are known as "field programmable" because, following manufacture, they enable users to modify the hardware to satisfy particular use case needs. This makes it possible to update features and correct bugs in-place, which is very helpful for remote deployments. Configurable logic blocks (CLBs) and a series of programmable interconnects are features of …
Published in Journal of Semiconductor Devices and Circuits · Vol. 11, Issue 3, 2024 · pp. 13–26 Read article
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An Efficient Color Method for Retrieving Color-based Images
Abstract: Image retrieval plays a vital role in many of the areas. CBIR is content-based image retrieval for browsing images from a large dataset. Image retrieval is used in many of the applications such as image processing, pattern recognition, military, medical fields and forensic fields. In the proposed image retrieval method, color method is used to extract the features and retrieve similar images based on similarity of features. In the color …
Published in Journal of Web Engineering & Technology · Vol. 1, Issue 2, 2014 · pp. 16–19 Read article
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A Survey of Multiwavelet Filtering Based Denoising Techniques for Mammographic Medical Images
Abstract: The digital mammographic imagery is often influenced by various types of noises and thus requires application of various filters to denoise the noise level in order to preserve the vital imagery contents. This evidently helps the medical practitioner to improve the image quality of the mammograms and helps them in giving accurate diagnosis. We have presented a survey of the popular denoising techniques used in the literature to achieve the …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 2, Issue 1, 2015 · pp. 1–4 Read article
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Segmentation Methods Applied on MR Medical Application
Abstract: AbstractImage segmentation techniques as applied in MRI of human brain are developing by leaps and bounds. The human brain is the most imaging design of the nature. Cancer and neurological problems are resolved using MR of the brain. The automatic diagnostic system starts with medical imaging, segmentation and analysis of the findings and then the final decisions which are further used to treat the patient. In the real world certain …
Published in Journal of Image Processing & Pattern Recognition Progress · Vol. 3, Issue 3, 2016 · pp. 30–38 Read article