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About

Dr. Sushanta Debnath is a dedicated researcher in the field of medical image analysis, with a primary focus on brain tumour detection and segmentation using advanced computational techniques. His work centers on developing innovative machine learning and clustering methods to improve the accuracy and reliability of three-dimensional tumour identification from medical scans. Dr. Debnath’s major contributions include the introduction of a memory-based learning approach for brain tumour segmentation (2019, 15 citations) and the development of a hybrid method combining contrast-enhanced fuzzy c-means (CEFCM) clustering with pixel-based voxel mapping (PBVMT) for enhanced 3D tumour detection (2020, 11 citations). He also proposed a two-phase detection framework incorporating confidence function evaluation to refine tumour localization (2021). With over 29 citations across his key works, Dr. Debnath’s research is steadily gaining recognition for its practical potential in improving diagnostic workflows. His notable achievements include pioneering the integration of fuzzy clustering with voxel-level mapping, offering a robust pathway toward fully automated brain tumour analysis.