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18 results for “tumor detection”
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Research ArticleOpen accessPhrase in the titleAn Improved Implementation of Brain Tumor Detection Using Segmentation Based on Neuro Fuzzy TechniqueS. Murugavalli, V. RajamaniImplementation of a neuro-fuzzy segmentation process of the MRI data is presented in this study to detect various tissues like white matter, gray matter, csf and tumor. The advantage of hierarchical self organizing map and fuzzy c means algorithms are used to classify the image layer by layer. The lowest level weight vector is achieved by the abstraction level. We … …Journal of Computer Science, Vol. 3, Issue 11 · 30 Nov 2007 · 7,107 accessesView PDFCite
Research ArticleOpen accessPhrase in the titleTowards an Explainable Approach: Hybrid Residual Network and SVM for Automated Brain Tumor Detection and ClassificationKamini Lamba, Shalli RaniThe abnormal growth of brain cells leads to tumor formation, which can be fatal if not detected and treated promptly. Given the complexity of brain tumors, early detection is critical in healthcare. Traditional radiology-based tumor detection is prone to human error and delays. Hence, a computer- assisted method is needed for accurate and efficient diagnosis. With the rapid advancements in … …Journal of Computer Science, Vol. 22, Issue 1 · 11 Feb 2026 · 1,427 accessesView PDFCite
Research ArticleOpen accessIn the keywordsFabrication and Testing of a Medical Surgical Instrument Capable of Detecting Simulated Embedded LumpsJavad Dargahi, Siamak Najarian, Reza Ramezanifard, Farhad Tabatabai GhomsheA novel endoscopic grasper is being fabricated and tested. This grasper can be used in detecting lumps or tumors in biological tissues. The detailed fabrication process of the tactile sensor has been discussed. Custom-made sensors were integrated with the jaws of the endoscopic grasper and objects with known tactile features were tested by the designed grasper. Different experiments were performed … …American Journal of Applied Sciences, Vol. 4, Issue 12 · 31 Dec 2007 · 6,999 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 abstractNon-Hodgkin Lymphoma Risk Grading Through the Pathological Data by Using the Optimized Convolutional Lymphnet ModelSivaranjini Nagarajan, Gomathi MuthuswamyDiagnosing Non-Hodgkin Lymphoma (NHL) is difficult and often requires specialised training and expertise as well as extensive morphological investigation and, in certain cases, costly immunohistological and genetic techniques. Computational approaches enabling morphological-based decision making are necessary for bridging the existing gaps. Histopathological images can be accurately classified using deep learning approaches, however data on NHL subtyping is limited. However, there … …Journal of Computer Science, Vol. 20, Issue 5 · 28 Feb 2024 · 4,545 accessesView PDFCite
EditorialOpen accessIn the abstractEditorial Commentary: Challenge of Non–AIDS-Defining Cancers (NADCs), Focusing on Trans Activation Response Element (TAR) RNA Embedding ExosomesLechuang Chen, Ge JinGlobally, 37.9 million people were living with HIV at the end of 2018 (Organization, 2018). Cancer is a major cause of mortality and morbidity in AIDS patients and chronically HIV-infected people. With the aid of combination Antiretroviral Therapy (ART), people living with HIV (PLWH) have a longer life span. However, because the virus is not completely eradicated, PLWH under antiretroviral … …American Journal of Immunology, Vol. 15, Issue 1 · 28 Nov 2019 · 6,657 accessesView PDFCite
Review ArticleOpen accessIn the abstractRoles of DLK1 in Liver Development and OncogenesisIsabella Kurnia Liem, Sibiri Indriyani, Msy Rulan Adnindya, Ahmad Azmi NasutionHepato Cellular Carcinoma (HCC) has an increased mortality rate in the last decade. Protein expression in HCC has similarities to the liver cells during the development process. One of the proteins expressions is Delta-Like 1 homolog (DLK1) that was found during liver development and oncogenesis. This permits the opportunity to study pathophysiology and signaling pathway of DLK1 and to find … …OnLine Journal of Biological Sciences, Vol. 17, Issue 4 · 23 Oct 2017 · 8,053 accessesView PDFCite
EditorialOpen accessIn the abstractNanotechnology: Engineering Materials for a Better 21st CenturyMeng Qiao, Xiyun Liu, Lei ZhangToday, we are living in the midst of a technological revolution, where nanotechnology is demonstrating a greater commitment to make people’s everyday lives better. The aim of nanotechnology is to create new materials with desired properties by engineering their nanoscale structures and components. One of the most important impacts of nanotechnology is in medical diagnosis and treatment. Cardiovascular diseases such … …Current Research in Nanotechnology, Vol. 5, Issue 1 · 26 Nov 2014 · 8,737 accessesView PDFCite
Research ArticleOpen accessIn the abstractA HYBRID FIREFLY ALGORITHM WITH FUZZY-C MEAN ALGORITHM FOR MRI BRAIN SEGMENTATIONMutasem K. AlsmadiImage processing is one of the essential tasks to extract suspicious region and robust features from the Magnetic Resonance Imaging (MRI). A numbers of the segmentation algorithms were developed in order to satisfy and increasing the accuracy of brain tumor detection. In the medical image processing brain image segmentation is considered as a complex and challenging part. Fuzzy c-means is … …American Journal of Applied Sciences, Vol. 11, Issue 9 · 10 Sep 2014 · 8,074 accessesView PDFCite
Research ArticleOpen accessIn the abstractPERFORMANCE ANALYSIS OF BRAIN TUMOR DIAGNOSIS BASED ON SOFT COMPUTING TECHNIQUESP. Shantha Kumar, P. Ganesh KumarComputed tomography images are widely used in the diagnosis of brain tumor because of its faster processing, avoiding malfunctions and suitability with physician and radiologist. This study proposes a new approach to automated detection of brain tumor. This proposed work consists of various stages in their diagnosis processing such as preprocessing, anisotropic diffusion, feature extraction and classification. The local binary … …American Journal of Applied Sciences, Vol. 11, Issue 2 · 27 Dec 2013 · 6,985 accessesView PDFCite