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Fazal Ahmed Talukdar has made significant contributions to the field of medical image analysis, with a primary focus on brain tumour detection and segmentation using advanced computational methods. His research centers on developing innovative machine learning and clustering techniques to improve the accuracy and efficiency of three-dimensional brain tumour identification from medical scans. Notably, his 2019 work on "Brain tumour segmentation using memory based learning method" has garnered 15 citations, showcasing its impact in the research community. Talukdar further advanced the field with his 2020 study introducing a novel combination of contrast enhanced fuzzy c-means (CEFCM) clustering and pixel based voxel mapping technique (PBVMT) for 3D brain tumour detection, which has received 11 citations. His 2021 paper on a two-phase detection method with confidence function evaluation demonstrates his ongoing commitment to refining diagnostic tools. Through these contributions, Talukdar has established himself as a dedicated researcher in biomedical imaging, offering practical solutions that enhance tumour localization and support clinical decision-making.