My research areas include computational medical imaging, machine lerning, image and multidimensional signal processing, visualization and augmented reality. The focus is on understanding the physics of imaging and to leverage machine learning algorithms to characterize tissues using physics based models of energy-tissue interaction thus, laying foundations of in situ functional histology. In due course along with my students and collaborators, we have investigated behaviour of ultrasonic and optical imaging signals interacting with different types of tissues, both in normal and pathological or diseased states. These have led to development of patient comfort centric non-invasive solutions for in situ histology of atherosclerotic vascular plaques, breast lesion, skin, and retina of the eye. Currently, we are working on developing deep and transfer learning techniques for analyzing multimodal medical imaging signals, understanding surgical informatics and effective visualization of such processes through augmented reality for clinical translation of research findings on the bed to equip clinicians with technology to deliver patient-comfort centric care.
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Designing Deep Neural High-Density Compression Engines for Radiology Images Raj A., Sathish R. , Sarkar T. , Sethuraman R. , Sheet D. By Circuits, Systems, and Signal Processing 42 643-682 (2023)
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Spatiotemporal Deep Networks for Detecting Abnormality in Videos Sharma M. K., Sheet D. , Biswas P. K. By Multimedia Tools and Applications 79 11237-11268 (2020)
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Frame-level global context modeling for detection and localization of abnormality Sharma M. K., Kumar V. , Sheet D. , Biswas P. K. By Multimedia Tools and Applications 1-26 (2023)
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Cholectriplet2021: A benchmark challenge for surgical action triplet recognition Nwoye C. I., Raviteja S. , Sathish R. , Balasubramanian V. , Sheet D. By Medical Image Analysis 86 102803--21 (2023)
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I m GROOT: a multi head multi GRaph netwOrk recognizing surgical actiOn Triplets Raviteja S., Sathish R. , Agrawal R. , De U. , Chakrabarti P. P., Sheet D. By Thirteenth Indian Conference on Computer Vision, Graphics and Image Processing 1-9 (2022)
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Verifiable and Energy Efficient Medical Image Analysis with Quantised Self-attentive Deep Neural Networks Sathish R., Khare S. R., Sheet D. By 25th International Conference on Medical Image Computing and Computer Assisted Intervention (MICCAI) W. Affordable AI and Healthcare for Resource Diverse Global Health (FAIR 2022) 178-189 (2022)
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CHAOS challenge-combined (CT-MR) healthy abdominal organ segmentation Kavur A. E., Sheet D. By Medical Image Analysis 69 101950-101950 (2021)
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Local instance and context dictionary-based detection and localization of abnormalities Sharma M. K., Sheet D. , Biswas P. K. By Machine Vision and Applications 32 1-21 (2021)
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Detection of Breast Cancer From Whole Slide Histopathological Images Using Deep Multiple Instance CNN Das K., Conjeti S. , Chatterjee J. , Sheet D. By IEEE Access 8 213502-213511 (2020)
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IDRiD: Diabetic Retinopathy Segmentation and Grading Challenge Porwal P., Sheet D. By Medical Image Analysis 59 101561-101561 (2020)
Principal Investigator
- Adani AI Research Fellowship Program
- AI-based CT Reconstruction for Low Dose, Low Resolution Scan
- Technology enhanced dissemination of specialized educational and research contents
on Engineering and Healthcare
Ph. D. Students
Abhishek Kumar
Area of Research: Medical image analysis, video processing, explainable models.
Abir Chowdhury
Area of Research: Medical imaging, Deep learning, Neuroimaging, Neuro information science
Alik Pramanick
Area of Research: Surgical information and audio-video event analysis
Anupam Borthakur
Area of Research: Federated Learning under Differential Privacy for Medical Imaging
Apoorva Srivastava
Area of Research: Biomedical Signal Processing
Ashraf Haroon Rashid
Area of Research: Multilinear Tensor Algebra for Deep Learning and Medical Imaging
Asim Manna
Area of Research: Deep Learning, Medical Imaging, Visual Hashing
Chinmay Kumar Behera
Area of Research: Deep Learning, Machine Vision, Industrial Process Monitoring
Dipayan Dewan
Area of Research: Neuro information science, Music cognition, Emotion analytics
Laveena Kewlani
Area of Research: Deep Learning, Federated Learning, Distributed Optimization
Maddimsetti Srinivas
Area of Research: Computational medical imaging and image analysis
Rachana Sathish
Area of Research: Computer assisted intervention, machine learning, medical image computing
Raj Krishan Ghosh
Area of Research: Computational ultrasonic imaging and deep learning
Seban James
Area of Research: Robotics
Sista Raviteja
Area of Research: Surgical Video Analytics and Surgical Informatics
MS Students
Rakshith Sathish
Area of Research: Explainable Deep Learning