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47 results for “Brain Image”
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Research ArticleOpen accessIn the abstractCascaded MNetV3UNet: A Lightweight Two-Stage Architecture for High-Precision Brain Tumor Segmentation in MRIMayuri Popat, Sanskruti PatelPrecise brain tumor segmentation is an essential but quite challenging process in MRI images because of their irregular shapes, heterogeneous appearance, and low contrast with surrounding tissues. While U-Net-based architectures have achieved significant success, their high computational complexity limits deployment on resource-constrained systems. In this study, a Novel two-stage cascaded architecture, MNetV3UNet, is introduced, which employs the light-weight MobileNetV3-Large as … …Journal of Computer Science, Vol. 22, Issue 2 · 23 Feb 2026 · 1,788 accessesView PDFCite
Research ArticleOpen accessIn the abstractIncorporation of Modified Region Growing into FCM Clustering for Extraction of Tumors in MR ImagesLovepreet Singh Brar, Jaget Singh, Bhawana Agrawal et al.Due to the tremendous growth of medical Magnetic Resonance (MR) images, it becomes an essential requirement for an automated extraction of diagnostically salient parts of the images to refine the transmission and storage process. Research method: This paper proposes an automated unsupervised machine learning segmentation technique named fuzzy c-means clustering based on modified region growing algorithm (RG-FCM) for the extraction … …Journal of Computer Science, Vol. 21, Issue 12 · 12 Feb 2026 · 1,477 accessesView PDFCite
Research ArticleOpen accessIn the abstractUsing Deep Learning to Support Clinical Decision-Making: The Case of Alzheimer’s Disease DiagnosisNawal Mohamed Bahy Eldin, Ghada A. El Khayat, Abeer A. AmerAlzheimer’s disease is a chronic, progressive brain disorder that leads to a gradual decline in memory and cognitive functions. In this study, N-VGG16, an advanced deep learning model, is proposed. The model builds upon the VGG16 architecture, incorporating key enhancements to improve its ability to classify neurodegenerative conditions. The model processes structural neuroimaging data using a refined pipeline that applies … …Journal of Computer Science, Vol. 21, Issue 10 · 11 Dec 2025 · 3,383 accessesView PDFCite
Research ArticleOpen accessIn the abstractA Vertical Stacking-Based Ensemble Deep Learning Model for Early Diagnosis of Alzheimer's Disease Using Multimodal MRI ScansParvatham Niranjan Kumar, Lakshmana Phaneendra MaguluriEarly detection of Alzheimer's Disease (AD) is crucial for timely interventions that can slow disease progression, enhance quality of life, and assist with future planning. Convolutional Neural Networks (CNNs) are an efficient method for processing image-based data. In this work, we used CNN-based deep learning models to extract structural information from structural MRI (sMRI) and brain neuron connectivity patterns from … …Journal of Computer Science, Vol. 21, Issue 6 · 14 Jun 2025 · 3,099 accessesView PDFCite
Review ArticleOpen accessIn the abstractA Survey of Generative AI ApplicationsRoberto Gozalo-Brizuela, Eduardo Eduardo Garrido MerchanGenerative AI has experienced remarkable growth in recent years, leading to a wide array of applications across diverse domains. In this study, we present a comprehensive survey of more than 350 generative AI applications, providing a structured taxonomy and concise descriptions of various unimodal and even multimodal generative AIs. The survey is organized into sections, covering a wide range of … …Journal of Computer Science, Vol. 20, Issue 8 · 24 May 2024 · 16,693 accessesView PDFCite
Research ArticleOpen accessIn the abstractEnhanced Postoperative Brain MRI Segmentation with Automated Skull Removal and Resection Cavity AnalysisSobha Xavier P., Sathish P. K., Raju G.Brain tumors present a significant medical challenge, often necessitating surgical intervention for treatment. In the context of postoperative brain MRI, the primary focus is on the resection cavity, the void that remains in the brain following tumor removal surgery. Precise segmentation of this resection cavity is crucial for a comprehensive assessment of surgical efficacy, aiding healthcare professionals in evaluating the … …Journal of Computer Science, Vol. 20, Issue 5 · 19 Mar 2024 · 5,697 accessesView PDFCite
Research ArticleOpen accessIn the abstractIdentification of the Presence of the "Swollen Shoot" Disease in Endemic Areas in Côte d'Ivoire Via Convolutional Neural NetworksCoulibaly Mamadou, Silue Kolo, Konan Hyacinthe Kouassi et al.The detection of Swollen Shoot disease and its control is one of the major objectives of research related to sustainable cocoa farming in Côte d'Ivoire. To contain the epidemic, the Cocoa Coffee Council (CCC) in collaboration with the National Agency for Support to Rural Development (ANADER) is responsible for prospecting and delimiting the infected areas as well as for uprooting … …American Journal of Engineering and Applied Sciences, Vol. 16, Issue 3 · 1 Oct 2023 · 6,064 accessesView PDFCite
Research ArticleOpen accessIn the abstractImage-Based Alzheimer's Disease Detection Using Pretrained Convolutional Neural Network ModelsNasser AlsadhanAlzheimer's disease is an untreatable, progressive brain disorder that slowly robs people of their memory, thinking abilities, and ultimately their capacity to complete even the most basic tasks. Among older adults, it is the most frequent cause of dementia. Although there is presently no treatment for Alzheimer's disease, scientific trials are ongoing to discover drugs to combat the condition. Treatments … …Journal of Computer Science, Vol. 19, Issue 7 · 28 Jun 2023 · 5,909 accessesView PDFCite
Research ArticleOpen accessIn the abstractAutism Detection from 2D Transformed EEG Signal using Convolutional Neural NetworkZahrul Jannat Peya, M. A. H. Akhand, Jannatul Ferdous Srabonee, Nazmul SiddiqueAutism Spectrum Disorder (ASD) is a neurodevelopmental disorder relating to speech complications, nonverbal and social communication, and repetitive behaviors. There is no remedy for ASD but early diagnosis, mediation, and supportive care can aid the development of language, conduct, and communication skills. As the cause of ASD is a neurodevelopmental disorder, its diagnosis based on brain function analyzing different brain … …Journal of Computer Science, Vol. 18, Issue 8 · 31 Jul 2022 · 7,921 accessesView PDFCite
Research ArticleOpen accessIn the abstractClassifications of Skull Fractures using CT Scan Images via CNN with Lazy Learning ApproachMd Moniruzzaman Emon, Tareque Rahman Ornob, Moqsadur RahmanClassification of skull fracture is a challenging task for both radiologists and researchers. Skull fractures result in broken pieces of bone, which can cut into the brain and cause bleeding and other injury types. So it is vital to detect and classify the fracture very early. In real world, often fractures occur at multiple sites. This makes it harder to … …Journal of Computer Science, Vol. 18, Issue 3 · 15 Mar 2022 · 9,005 accessesView PDFCite