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10 results for “Lesion Segmentation”
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Research ArticleOpen accessPhrase in the titleAdvancing Stroke Lesion Segmentation With U-Net Variants: Classical, Transfer Learning, and MRI Sequence-Specific Customized ApproachesSonia Flora Panesar, Amit P. GanatraIschemic stroke, caused by restricted cerebral blood flow, is a leading cause of death and disability worldwide. Accurate segmentation of stroke lesions in MRI is essential for timely diagnosis but remains labor-intensive when done manually. This study presents a comparative evaluation of three U-Net variants for automated ischemic stroke lesion segmentation using the ISLES 2022 dataset: (1) Classical U-Net with … …Journal of Computer Science, Vol. 22, Issue 2 · 27 Feb 2026 · 1,791 accessesView PDFCite
Research ArticleOpen accessIn the keywordsA Comprehensive Review on Skin Cancer Detection Strategies using Deep Neural NetworksAkepati Sankar Reddy, Gopinath M. PSkincancer is a deadly malignancy. Incomplete D.N.A. repair in skin cells causeshereditary mutations and cancer. Early skin cancer is easier to treat since itspreads slowly to other body areas. As a result, the optimal time to find it isduring its infancy. Because of the rising frequency of skin cancer, the highmortality rate, and the high cost of medical treatment, early … …Journal of Computer Science, Vol. 18, Issue 10 · 5 Oct 2022 · 6,400 accessesView PDFCite
Research ArticleOpen accessIn the abstractLeveraging Modified Cascaded Fully Convolutional Neural Networks and Optimized Swin U-Net for Liver Lesion PredictionSugandha Chakraverti, Tejaswi Khanna, Vijay ShuklaLiver lesions are abnormal growths that can develop for various reasons, some of which are noncancerous (benign) while others are cancerous. Machine learning and, deep learning techniques are employed for liver health assessment and lesion detection, but the quality and, diversity of training data can hinder the performance, leading to overfitting or underfitting. These models often need extensive pre-processing and … …Journal of Computer Science, Vol. 22, Issue 10 · 8 Oct 2026 · 372 accessesView PDFCite
Research ArticleOpen accessIn the abstractPolar Disentangled Non-Local Convolutional Neural Network for Skin Cancer Classification Using Dermoscopy ImagesUsha Thirugnanam, Nalini JosephSkin cancer classification is the process of identifying and categorizing various types of skin lesions into cancerous and non-cancerous. This process is performed to achieve accurate detection, which minimizes the risk of severe health complications. However, classifying the severity of skin lesion images is a difficult task because of subtle and overlapping visual patterns, which could lead to inaccurate performance. … …Journal of Computer Science, Vol. 22, Issue 6 · 16 Jun 2026 · 1,207 accessesView PDFCite
Research ArticleOpen accessIn the abstractAuto Weight Dilated Convolutional Ensemble Network for the Severity Analysis of Lung Cancer in CT ImagesL. Sandhya, K. MarimuthuLung cancer is one of the world's leading causes of morbidity and mortality; improving patient outcomes requires an early and precise diagnosis. Lesion and tumor segmentation remains a challenging task in CT images due to their inherent imaging limitations, such as the small size of nodules, heterogeneous textures, blurry boundaries, and adjacent structures, leading to misclassification and difficulty in delineating … …Journal of Computer Science, Vol. 22, Issue 1 · 9 Feb 2026 · 1,541 accessesView PDFCite
Research ArticleOpen accessIn the abstractOptimized Fractal Fusion Driven Deep Neural Network: An Efficient Hybrid Methodology for Disease Detection and Classification in Plant LeavesDeepkiran Munjal, Mrinal Pandey, Laxman SinghPlant diseases and pest attacks are among the major issues in agriculture, which have a great impact on crop growth and yield. Early and correct detection of these diseases is vital for effective management and keeping plant health at the desired level. This research proposes a new method for detection and classification of plant diseases, the Optimized Fractional Fusion Deep … …Journal of Computer Science, Vol. 21, Issue 12 · 8 Jan 2026 · 2,223 accessesView PDFCite
Research ArticleOpen accessIn the abstractNew and Efficient Features for Skin Lesion Classification based on SkeletonizationYoussef Filali, Hasnae El Khoukhi, My Abdelouahed Sabri et al.This paper presents a new approach to detect and classify skin lesions for melanoma diagnosis with high accuracy. Skin lesion detection is based on an image decomposition into two components using the Partial Differential Equation (PDE). The first component that sufficiently preserves the contour is thus exploited to have an adequate segmentation of image lesion while the second component provides … …Journal of Computer Science, Vol. 15, Issue 9 · 2 Sep 2019 · 8,028 accessesView PDFCite
Research ArticleOpen accessIn the abstractAUTOMATIC SEGMENTATION OF SKIN LESIONS USING HISTOGRAM THRESHOLDINGNidhal Khdhair El Abbadi, Abbas Hussien MiryAutomatic lesion segmentation is an important part of computer-based image analysis of pigmented skin lesions. Currently, there is a great interest in the development of Computer-Aided Diagnosis (CAD) systems for dermoscopic images. The segmentation step is one of the most important ones, since its accuracy determines the eventual success or failure of a CAD system. This study introduced new method … …Journal of Computer Science, Vol. 10, Issue 4 · 19 Dec 2013 · 7,559 accessesView PDFCite
Research ArticleOpen accessIn the abstractWavelet Transform Based Automatic Lesion Detection in Cervix Images Using Active ContourP. S. Rama Praba, H. RanganathanColposcopy is a medical diagnostic procedure to examine an illuminated, magnified view of the cervix by a colposcope. Most cases of cervical cancer can be prevented through screening programs aimed at detecting precancerous lesions. Colposcopy cervical images are acquired in raw form which contains major cervix lesions, regions outside the cervix and parts of the imaging devices such as speculum. … …Journal of Computer Science, Vol. 9, Issue 1 · 31 Jan 2013 · 7,783 accessesView PDFCite
Research ArticleOpen accessIn the abstractDermoscopic Image Segmentation using Machine Learning AlgorithmL. Padma Suresh, K.L. Shunmuganathan, S.H. Krishna VeniProblem statement: Malignant melanoma is the most frequent type of skin cancer. Its incidence has been rapidly increasing over the last few decades. Medical image segmentation is the most essential and crucial process in order to facilitate the characterization and visualization of the structure of interest in medical images. Approach: This study explains the task of segmenting skin lesions in … …American Journal of Applied Sciences, Vol. 8, Issue 11 · 7 Oct 2011 · 7,342 accessesView PDFCite