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 …

Deep learning-based ensemble model for brain tumor segmentation using multi-parametric MR scans

S Das, S Bose, GK Nayak, S Saxena - Open Computer Science, 2022 - degruyter.com
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 …

Effect of learning parameters on the performance of the U-Net architecture for cell nuclei segmentation from microscopic cell images

B Jena, D Digdarshi, S Paul, GK Nayak, S Saxena - Microscopy, 2023 - academic.oup.com
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 …

WU-Net++: A novel enhanced Weighted U-Net++ model for brain tumor detection and segmentation from multi-parametric magnetic resonance scans

S Das, R Dubey, B Jena, LW Tsai, S Saxena - Multimedia Tools and …, 2024 - Springer
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 …

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 …

EDLNet: ensemble deep learning network model for automatic brain tumor classification and segmentation

SR Vinta, PV Chintalapati, GR Babu… - Journal of …, 2024 - Taylor & Francis
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 …

A Lightweight Attention based MobileNetv2 Model for Brain Tumor Segmentation and Severity of Tumor Classification using Support Vector Machine

D Pavithra, R Nidhya, C Vinothini, M Murugaiyan - 2023 - researchsquare.com
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 …

Light-UNet++: A Simplified U-NET++ Architecture for Multimodal Biomedical Image Segmentation

S Das, S Bose, R Jain, M Rout - 2023 IEEE International …, 2023 - ieeexplore.ieee.org
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 …

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 …

Analysis of Pneumonia detection in X-ray images using different filters based Convolution Neural Networks

S Das, S Samanta, M Rout - 2023 OITS International …, 2023 - ieeexplore.ieee.org
With recent advances and diversity of medical image acquisition technologies and
processing, artificial intelligence-based deep learning has proven its indispensable image …