Intelligent Biomedical Image Analysis
Intelligent Biomedical Image Analysis
Medical imaging inherently contains imperfections and is therefore an appropriate domain for applying computational intelligence. With the growing availability of large volumes of multimodal healthcare data online, automated processing is increasingly relevant. Manual delineation and processing are expensive, biased, and slow. Artificial intelligence, including machine learning and deep learning, offers a powerful solution. AI provides assistive intelligence to healthcare professionals as they develop cost-effective, fast, and viable solutions to complex decision-making problems.
This talk outlines AI's role across several aspects of healthcare, including classification, segmentation, and survival prediction, and explores resource-efficient hybrid models. We introduce a deformable deep net for efficient segmentation. We discuss applications that use multimodal imaging spanning X-ray, CT, and fundus imaging to address specific diseases.
Sushmita Mitra is a full professor at the Machine Intelligence Unit (MIU), Indian Statistical Institute, Kolkata. From 1992 to 1994 she was in the RWTH, Aachen, Germany as a DAAD Fellow. She was a Visiting Professor in the Computer Science Departments of the University of Alberta, Edmonton, Canada; Meiji University, Japan; and Aalborg University Esbjerg, Denmark. Dr. Mitra received the National Talent Search Scholarship (1978-1983) from NCERT, India, the University Gold Medal in 1988, the IEEE TNN Outstanding Paper Award in 1994 for her pioneering work in neuro-fuzzy computing, the CIMPA-INRIA-UNESCO Fellowship in 1996, Fulbright-Nehru Senior Research Fellowship in 2018-2020, and J. C. Bose National Fellowship in 2021-2026. She was the INAE Chair Professor during 2018-2020. Dr. Mitra has been awarded the prestigious J. C. Bose Grant, 2026.
Dr. Mitra is the author of the books ``Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing" and ``Data Mining: Multimedia, Soft Computing, and Bioinformatics" published by John Wiley, and ``Introduction to Machine Learning and Bioinformatics", Chapman & Hall/CRC Press, beside a host of other edited books. Dr. Mitra has guest edited special issues of several journals, is an Associate Editor of ``IEEE/ACM Trans. on Computational Biology and Bioinformatics", ``Information Sciences", ``Proceedings of the INSA", ``Computers in Biology and Medicine", ``IEEE Trans. on Fuzzy Systems", ``Neural Networks", a Founding Associate Editor of ``Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (WIRE DMKD)", and a Senior Associate Editor of ``Sadhana". She has more than 150 research publications in referred international journals.
Dr. Mitra is a Fellow of the IEEE, The World Academy of Sciences (TWAS), Indian National Science Academy (INSA), International Association for Pattern Recognition (IAPR), Asia-Pacific Artificial Intelligence Association (AAIA), and Fellow of the Indian Academy of Sciences (IASc), Indian National Academy of Engineering (INAE), and The National Academy of Sciences, India (NASI). She serves as a Member of the Inter-Academy Panel for Women in STEMM, and a Member of the Equality, Diversity and Inclusion Groups of CAETS and IAPR. Dr. Mitra is a Member, Scientific Advisory Committee, National Institute for Theoretical and Computational Sciences (NITheCS), 2025-2028. She has visited more than 30 countries as a Plenary/Invited Speaker or an academic visitor. She served in the capacity of General Chair, Program Chair, Tutorial Chair, of many international conferences; was the Chair, IEEE Kolkata Section (2021-2022) and an IEEE CIS Distinguished Lecturer. Her current research interests include data science, machine learning, soft computing, medical image processing, and Bioinformatics.
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- Rua Marquês de São Vicente, 225,
- no bairro da Gávea, na Zona Sul do Rio de Janeiro
- Rio de Janeiro, Rio de Janeiro
- Brazil 22451-900
- Building: Cardeal Leme
- Room Number: 401L
- Starts 26 September 2026 03:00 AM UTC
- Ends 07 October 2026 03:00 AM UTC
- No Admission Charge
Speakers
Sushmita of Indian Statistical Institute, Kolkata
Intelligent Biomedical Image Analysis
Medical imaging inherently entails imperfections and is, therefore, an appropriate domain for the application of computational intelligence. With the growing availability of large volumes of multimodal healthcare data online, their automated processing is increasingly relevant today. Manual delineation and processing are expensive, biased, and slow. Here lies the utility of artificial intelligence, encompassing machine learning and deep learning. The role of AI is to provide assistive intelligence to healthcare professionals in their efforts to develop cost-effective, fast, and viable solutions to complex decision-making problems.
This talk outlines the role of AI across several aspects of healthcare, including classification, segmentation, and survival prediction, and explores resource-efficient hybrid models. A deformable deep net is introduced for efficient segmentation. We discuss applications that use multimodal imaging spanning X-ray, CT, and fundus imaging to address specific diseases.
Biography:
Sushmita Mitra is a full professor at the Machine Intelligence Unit (MIU), Indian Statistical Institute, Kolkata. From 1992 to 1994 she was in the RWTH, Aachen, Germany as a DAAD Fellow. She was a Visiting Professor in the Computer Science Departments of the University of Alberta, Edmonton, Canada; Meiji University, Japan; and Aalborg University Esbjerg, Denmark. Dr. Mitra received the National Talent Search Scholarship (1978-1983) from NCERT, India, the University Gold Medal in 1988, the IEEE TNN Outstanding Paper Award in 1994 for her pioneering work in neuro-fuzzy computing, the CIMPA-INRIA-UNESCO Fellowship in 1996, Fulbright-Nehru Senior Research Fellowship in 2018-2020, and J. C. Bose National Fellowship in 2021-2026. She was the INAE Chair Professor during 2018-2020. Dr. Mitra has been awarded the prestigious J. C. Bose Grant, 2026.
Dr. Mitra is the author of the books ``Neuro-Fuzzy Pattern Recognition: Methods in Soft Computing" and ``Data Mining: Multimedia, Soft Computing, and Bioinformatics" published by John Wiley, and ``Introduction to Machine Learning and Bioinformatics", Chapman & Hall/CRC Press, beside a host of other edited books. Dr. Mitra has guest edited special issues of several journals, is an Associate Editor of ``IEEE/ACM Trans. on Computational Biology and Bioinformatics", ``Information Sciences", ``Proceedings of the INSA", ``Computers in Biology and Medicine", ``IEEE Trans. on Fuzzy Systems", ``Neural Networks", a Founding Associate Editor of ``Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery (WIRE DMKD)", and a Senior Associate Editor of ``Sadhana". She has more than 150 research publications in referred international journals.
Dr. Mitra is a Fellow of the IEEE, The World Academy of Sciences (TWAS), Indian National Science Academy (INSA), International Association for Pattern Recognition (IAPR), Asia-Pacific Artificial Intelligence Association (AAIA), and Fellow of the Indian Academy of Sciences (IASc), Indian National Academy of Engineering (INAE), and The National Academy of Sciences, India (NASI). She serves as a Member of the Inter-Academy Panel for Women in STEMM, and a Member of the Equality, Diversity and Inclusion Groups of CAETS and IAPR. Dr. Mitra is a Member, Scientific Advisory Committee, National Institute for Theoretical and Computational Sciences (NITheCS), 2025-2028. She has visited more than 30 countries as a Plenary/Invited Speaker or an academic visitor. She served in the capacity of General Chair, Program Chair, Tutorial Chair, of many international conferences; was the Chair, IEEE Kolkata Section (2021-2022) and an IEEE CIS Distinguished Lecturer. Her current research interests include data science, machine learning, soft computing, medical image processing, and Bioinformatics.
Agenda
This talk outlines the role of AI across several aspects of healthcare, including classification, segmentation, and survival prediction, and explores resource-efficient hybrid models. A deformable deep net is introduced for efficient segmentation. We discuss applications that use multimodal imaging spanning X-ray, CT, and fundus imaging to address specific diseases.