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Brain tumor segmentation and overall survival period prediction in glioblastoma multiforme using radiomic features
S Das, S Bose, GK Nayak… - Concurrency and …, 2022 - Wiley Online Library
Glioblastoma multiforme (GBM or glioblastoma) is a fast‐growing glioma that are the most
invasive type of glial tumors, rapidly growing and commonly spreading into nearby brain …
invasive type of glial tumors, rapidly growing and commonly spreading into nearby brain …
Deep learning-based ensemble model for brain tumor segmentation using multi-parametric MR scans
Glioma is a type of fast-growing brain tumor in which the shape, size, and location of the
tumor vary from patient to patient. Manual extraction of a region of interest (tumor) with the …
tumor vary from patient to patient. Manual extraction of a region of interest (tumor) with the …
Effect of learning parameters on the performance of the U-Net architecture for cell nuclei segmentation from microscopic cell images
Nuclei segmentation of cells is the preliminary and essential step of pathological image
analysis. However, robust and accurate cell nuclei segmentation is challenging due to the …
analysis. However, robust and accurate cell nuclei segmentation is challenging due to the …
WU-Net++: A novel enhanced Weighted U-Net++ model for brain tumor detection and segmentation from multi-parametric magnetic resonance scans
Brain tumor detection and segmentation from multi-parametric magnetic resonance (MR)
scans are crucial for the prognosis and treatment planning of brain tumor patients in current …
scans are crucial for the prognosis and treatment planning of brain tumor patients in current …
A survey: Brain tumor detection using MRI image with deep learning techniques
C Kanumuri, CHR Madhavi - Smart and Sustainable …, 2022 - Wiley Online Library
Brain tumors can occur anywhere in the brain and greatly vary in size and morphology.
These tumors are frequently disseminated and without contrast. As a result, a challenging …
These tumors are frequently disseminated and without contrast. As a result, a challenging …
EDLNet: ensemble deep learning network model for automatic brain tumor classification and segmentation
The brain's abnormal and uncontrollable cell partitioning is a severe cancer disease. The
tissues around the brain or the skull induce this tumor to develop spontaneously. For the …
tissues around the brain or the skull induce this tumor to develop spontaneously. For the …
A Lightweight Attention based MobileNetv2 Model for Brain Tumor Segmentation and Severity of Tumor Classification using Support Vector Machine
Brain tumors are lumps of aberrant tissue that can develop into cancer and have a
significant negative influence on a person's health. MRI scans of the brain can reveal them …
significant negative influence on a person's health. MRI scans of the brain can reveal them …
Light-UNet++: A Simplified U-NET++ Architecture for Multimodal Biomedical Image Segmentation
Images have been the most comprehensive data source in the field of healthcare but have
likewise been one of the most challenging ones to analyze. Deep Learning, since its …
likewise been one of the most challenging ones to analyze. Deep Learning, since its …
Glioma segmentation using hybrid filter and modified African vulture optimization
B Kuntiyellannagari, B Dwarakanath - Bulletin of Electrical Engineering …, 2025 - beei.org
Accurate brain tumor segmentation is essential for managing gliomas, which arise from
brain and spinal cord support cells. Traditional image processing and machine learning …
brain and spinal cord support cells. Traditional image processing and machine learning …
Analysis of Pneumonia detection in X-ray images using different filters based Convolution Neural Networks
With recent advances and diversity of medical image acquisition technologies and
processing, artificial intelligence-based deep learning has proven its indispensable image …
processing, artificial intelligence-based deep learning has proven its indispensable image …