Mohammed Ansar Mohammed Ansar
Project Research Scientist-i @Indian Institute Of Information Technology Design & Manufacturing Kancheepuram
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WORK HISTORY
Project Research Scientist-i @Indian Institute Of Information Technology Design & Manufacturing Kancheepuram
IN
Design and evaluation of diagnostic accuracy of bimodal multispectral high-resolution microendoscopy imaging of premalignant oral lesion in comparison to visual inspection in scree-positive patients
EDUCATION
Harvey Biomedical
Biomedical/Medical Engineering
Cochin University of Science and Technology
Bachelor of Technology - BTech, Instrumentation Technology/Technician
ABOUT MOHAMMED ANSAR MOHAMMED ANSAR
I am a dedicated Computer Vision Engineer and Project Research Scientist-I (Non-Medical), currently contributing to ICMR-funded research focused on AI-enabled medical imaging and diagnostic device development at Kancheepuram.My work involves the design and evaluation of advanced imaging systems for early cancer detection, including the project titled “Opto-electrical transvaginal imaging probe for pre-invasive cervical cancer diagnosis” and a recently undertaken project, “Design and evaluation of diagnostic accuracy of bimodal multispectral high-resolution microendoscopy imaging of premalignant oral lesions in comparison to visual inspection in screen-positive patients.”Operating at the intersection of medical imaging, computer vision, and medical device R&D, I develop intelligent imaging pipelines and vision-based algorithms to enhance diagnostic accuracy and support clinical decision-making. My interests lie in translating research into deployable healthcare technologies that address real-world screening and diagnostic challenges.I am particularly motivated by interdisciplinary collaboration and the application of AI, machine vision, and embedded systems to improve early detection outcomes in oncology and public health.With hands-on experience in multi-spectral imaging, real-time image processing, and AI-assisted diagnostic tools, I specialize in building robust, accurate, and user-friendly computer vision systems for healthcare applications.I’m passionate about using computer vision and machine learning to solve real-world medical challenges and improve patient care. I actively seek collaborations with researchers, engineers, and healthcare professionals to push the boundaries of medical diagnostics.
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