Drew Williamson is a board certified pathologist who is focusing on pathology AI. Drew is part of the Emory Empathetic AI for Health Institute and the AI.Humanity initiative at Emory University, Atlanta, USA. We will hear all about his exciting research on clinical translation of Pathology AI.

A multimodal generative AI copilot for human pathology

Jayashree kalpathy Cramer is the chief of the Division of Artificial Medical Intelligence in Ophthalmology at the University of Colorado (CU) School of Medicine. Jayashree is focusing on translational artificial intelligence (AI) for effective patient care practices at the Sue Anschutz-Rodgers Eye Center.

Saad Nadeem is an assistant attending computer scientist at Memorial Sloan Kettering Cancer Center with dual appointments in the Departments of Medical Physics and Pathology. He is also an adjunct assistant professor in the Department of Applied Mathematics & Statistics at Stony Brook University. Saad focuses on multimodal and multiscale analysis of biomedical data to improve patient outcomes.

DeepLIIF

MICCAI Student Board

Mission

The MICCAI Student Board (MSB) represents student interests within the MICCAI society, and aims to stimulate the involvement of students within the MICCAI community. The MSB enhances student networking in the community, engages students in the MICCAI society, and advises the MICCAI board on matters of relevance for students. The MSB organises social and professional and student events during the MICCAI period, in collaboration with local organisers, and maintains the MICCAI Educational Initiative.

Islem Rekik is the Director of the Brain And SIgnal Research and Analysis (BASIRA) laboratory (http://basira-lab.com/) and an Associate Professor at Imperial College London (Innovation Hub I-X). Together with BASIRA members, she conducted more than 100 cutting-edge research projects cross-pollinating AI and healthcare —with a sharp focus on brain imaging and neuroscience. She is also a co/chair/organizer of more than 25 international first-class conferences /workshops /competitions (e.g., Affordable AI 2021-22, Predictive AI 2018-2024, Machine Learning in Medical Imaging 2021-24, WILL competition 2021-23). Dr Rekik has been awarded prestigious international research fellowships including the EU Marie-Curie Fellowship in 2019 and the TUBITAK 2232 for Outstanding Experienced Researchers during 2020-2022. In addition to her 150+ high-impact publications, she is a strong advocate of equity, inclusiveness and diversity in research. She is the former president of the Women in MICCAI (WiM), the co-founder of the international RISE Network to Reinforce Inclusiveness & diverSity and Empower minority researchers in Low-Middle Income Countries (LMIC) and a committee member of the AFRICAI network. She is in the organizing committee of MICCAI 2022 (Singapore), 2023 (Vancouver), 2024 (Marrakesh) and 2025 (South Korea).

Graph Neural Networks in Network Neuroscience

Akshay Chaudhari is an Assistant Professor in the Integrative Biomedical Imaging Informatics at the Department of Radiology in Stanford University, USA. He leads the Machine Intelligence in Medical Imaging research group and has a primary research interest at the intersection of artificial intelligence and medical imaging. He also serves as the Associate Director of Research and Education at the Stanford AIMI Center. Adapted large language models can outperform medical experts in clinical text summarization

Prof. Rajendra Pratap Gupta is a leading public policy expert with over a decade of experience. Rajendra has worked with the World Economic Forum in the past & has served as an advisor to the Union Health Minister of India. He is focusing on designing digital health policies to make healthcare AI-ready.

Prof. Hamid Tizhoosh explores the applications of artificial intelligence (AI) in medicine, particularly in medical image analysis and cross relations to other patient data such as molecular, laboratory and textual data. His research is currently focused on search and matching in archives of patient data. Foundation Models for Histopathology—Fanfare or Flair

Creating an atlas of normal tissue for pruning WSI patching through anomaly detection

Prof. Kevin Zhou is a Distinguished Professor and Founding Executive Dean of School of Biomedical Engineering, University of Science and Technology of China (USTC). Before this, Dr. Zhou was a Principal Expert and a Senior R&D Director at Siemens Healthcare Research. He has been elected as a fellow of several top societies such as AIMBE, IEEE and MICCAI. Prof. Zhou serves the MICCAI society as a board member and currently focuses on generative AI for medical imaging.

Alexander Hann is a gastroenterologist at Uniklinik Würzburg, Germany and holds a professorship for digital transformation in gastroenterology, which focuses on AI support for endoscopic imaging.

Damini Dey is a professor in Biomedical Sciences at Cedars Sinai Medical center, Los Angeles, USA. Professor Dey focuses on automated derivation of imaging measures from noninvasive cardiac image data, clinical implementation of novel automated computer processing algorithms, and the application of these tools to solve key clinical problems. Her success stories include QFAT and AutoPlaque softwares.

Enzo Ferrante is a Research Scientist at Universidad Nacional del Litoral in Santa Fe, Argentina. Enzo focuses on machine learning methods for biological and medical image analysis, including domain adaptation and segmentation with anatomical priors.

Addressing fairness in artificial intelligence for medical imaging

Professor Randy Ellis is a legendary figure within the computer-assisted orthopedic surgery community. His primary appointment is in the School of Computing with additional appointments at the Mechanical and Materials Engineering, Surgery, and Biomedical and Molecular Sciences at the Queen's University, Canada.  He has been a Fellow of several organizations such as IEEE, American Society for Mechanical Engineering (ASME) etc.

Prof. Jochen Lennerz is the Medical Director of the Center for Integrated Diagnostics at the Massachusetts General Hospital, USA. He is a board-certified pathologist by training and has professorship appointments at Harvard medical School. Prof. Lennerz co-organized the Data4Health 2023 conference in Berlin with the health minister of Germany Prof. Karl Lauterbach.

Data4Health 2023 Berlin

Neel Dey is a postdoctoral researcher at MIT CSAIL in Polina Golland’s Medical Vision Group, where he is building dense representation learning and domain randomization methods for data and compute-efficient learning tasks. Neel got his Ph.D. from New York University under Guido Gerig where he worked on generative models and inverse problems in medical image analysis.

E(3) x SO(3) - Equivariant Networks for Spherical Deconvolution in Diffusion MRI

AnyStar: Domain randomized universal star-convex 3D instance segmentation

Maria Zuluaga is an assistant professor in the Data Science department at EURECOM, France. Additionally Maria holds a junior chair at the 3IA Institute Côte d’Azur and also a visiting Senior Lecturer at King’s College London. She focuses on machine learning techniques that can be safely deployed in high risk domains, such as healthcare, by addressing data complexity, low tolerance to errors and poor reproducibility.

From Accuracy to Reliability and Robustness in Cardiac Magnetic Resonance Image Segmentation: A Review

Interactive Medical Image Segmentation Using Deep Learning With Image-Specific Fine Tuning

Dr. Heather Couture is a Consultant, a Researcher and a Writer. Heather is a consultant and owner of Pixel Scientia Labs. She works on a variety of interdisciplinary R&D projects and regularly blogs about the advances of AI in LinkedIn.

Pieter De Backer leads the Innotech department at Orsi, a training and innovation centre in minimal invasive & robotic surgery located in Gent, Belgium. Pieter's team focuses primarily on developing AI based surgical systems and patient-specific 3D modeling.

Camila Gonzalez is a PostDoc in Stanford University, USA. Camila finished her PhD on medical continual learning in TU Darmstadt in March 2023, while accumulating multiple awards along the process. She is also the outgoing president of MICCAI Student Board, presiding it for the last 2 years.

Lifelong nnU-Net: a framework for standardized medical continual learning

Shek Azizi is a senior research scientist at Google DeepMind. Her research is focused on translational AI with tangible clinical impact. She designs foundation models for biomedical applications. She has led the moonshot project behind Med-PaLM, Med-PaLM 2 and Med-PaLM M.

Large Language Models Encode Clinical Knowledge

Daniel Hashimoto is an assistant Professor of Surgery at the Hospital of the University of Pennsylvania, USA. Dan has developed multiple computer vision algorithms for the analysis of surgical video, led international consensus on defining ground truth for the annotation of surgical video, and worked to define metrics to assess performance of AI algorithms on surgical tasks. His work has been published in the New England Journal of Medicine, Nature Biotechnology, Annals of Surgery, and other journals. He is editor of the textbook Artificial Intelligence in Surgery: Understanding the Role of AI in Surgical Practice. He is also heavily involved in MICCAI society with a focused attention to CLINICCAI.

Prof. Stephen Gilbert is a professor in Medical Device Regulatory Science at the Else Kröner Fresenius Center for Digital Health in TU Dresden, Germany. His research goal is to advance regulatory requirements, especially for software as a medical device and artificial intelligence in medical devices.

Papers we discussed: Large language model AI chatbots require approval as medical devices

Continuous Improvement of Digital Health Applications Linked to Real-World Performance Monitoring: Safe Moving Targets?

Prof. Nitika Pai is an Associate Professor in the Department of Medicine at the McGill University, Canada. Her global implementation research program in Canada, India and South Africa is primarily focused on point-of-care diagnostics for HIV and associated co-infections. Her research informs domestic and global policy on point-of-care diagnostics.

Uta Schmidt-Strassburer is the scientific director of the Advanced Oncology study program at the Ulm university Germany. She is also a fellow podcaster, running the bilingual "caring and sharing" podcast on advanced oncology. Over the years, Uta has developed a critical appreciation towards oncology AI.

Prof. Swapnil Rane is a Pathologist by training, and currently a professor in Tata Memorial Center, Mumbai, India. He is instrumental in bringing forward the AI and digital pathology research from India, especially the ongoing project of Indian Image BioBank.

Dr. Ishita Barua leads AI in healthcare at Deloitte, with a focus on improving equity and outcomes in digital health. She is a medical doctor and PhD by training with expertise in application and clinical validation of AI in Medicine. Ishita has won numerous awards including Top 50 women in tech and top 30 women in Norway shaping the field of artificial intelligence.

Prof. Raphael Sznitman is the Director of the ARTORG center for Biomedical Engineering at the University of Bern (Switzerland). Raphael is interested in computational vision, probabilistic methods and statistical learning, applied to applications in medical imaging.

Instead of having a guest, Anirban and Henry just chit chats about the background stories, lessons learned, our ever-evolving thoughts etc. in the 50th episode of AI-ready Healthcare.

Prof. Nikos Paragios is a senior researcher focusing on computer vision and medical imaging. Nikos is a professor of Computer Science and Applied mathematics at CentraleSupélec, an affiliated scientific leader at INRIA while serving as the editor in chief of the Computer Vision and Image Understanding Journal. Nikos is also the founder and CEO of TheraPanacea, provider of AI-powered software for more efficient radiotherapy workflow.

Lene Topp is passionate about designing and delivering training and other capacity building activities primarily for researchers looking to increase the impact of their research in policy sectors. Until February 2023, she worked in the European Union's Joint Research Center focusing on the "Science4Policy" gap. Among many other things, she led the development of Smart4Policy researchers tool to help researchers working in science-for-policy reflect on their level of competence. .

Prof. Stefanie Speidel is a full professor for “Translational Surgical Oncology” and director at the National Center for Tumor Diseases Dresden since 2017. She is an elected board member of the MICCAI society. She is well-know for her research on Surgical Data Science, data-driven surgical training and context-aware human-machine collaboration in the operating room.

Prof. Sotirios Tsaftaris is the Chair in Machine Learning and Computer Vision at the University of Edinburgh, UK. He also holds the Canon Medical/Royal Academy of Engineering Research Chair in Healthcare AI. He is also a Turing Fellow with the Alan Turing Institute and an ELLIS Fellow. 

Pascal Wettstein is the owner of QDC GmbH. He is the self-proclaimed "SME safari guide in the regulatory jungle." I highly recommend his rather sarcastic LinkedIn posts on European Medical Device Regulations. Beyond Europe, he has extensive knowledge about the 510K regulations in FDA.

Sharib Ali is the lecturer at School of Computing in the University of Leeds, UK. He has a PhD from France and spent time as a PostDoc in Germany as well as in Oxford before starting as the PI in Leeds. He is well-known for his research on AI for analyzing Endoscopic images.

The two articles we discussed in this episode:

1. Where do we stand in AI for endoscopic image analysis? Deciphering gaps and future directions.

2. A multi-centre polyp detection and segmentation dataset for generalisability assessment.

Juan Verde is a Digestive and hepato-biliary-pancreatic Surgeon by training with a deep passion for surgical AI. Juan is currently working as a full-time Research Associate at the Institute of Image-Guided Surgery in Strasbourg, France.

Prof. Jocelyne Troccaz is a legendary figure in image-guided medical robotics, with a career spanning across four decades. She covered a broad spectrum of applications including urology, radiotherapy, cardiac surgery, orthopedics to name a few. She won numerous awards. Some highlights include MICCAI 2022 enduring impact award and the highest French decoration (Légion d’Honneur).

Monir El Azzouzi created the Easy Medical Device ecosystem, that includes blogs, podcasts, YouTube videos and regular updates in LinkedIn. His mission is to make the process of bringing Compliant Medical Device to the Market easier. He has a deep understanding of the Medical Device Regulations at European Union.

Easy Medical Device: https://easymedicaldevice.com/home/

Dr. Monika Sonu is a physician by training and Digital Health Entrepreneur by passion. She is the CEO of Health Innovation Toolbox. Monika drives digitisation of the operating models, functions and workflows within hospitals. She is also interested in creating better patient experience. She is named as HIMSS Future50 Innovation Leader in 2021.

Professor Purang Abolmaesumi is a Professor in University of British Columbia. He is very well-known within the MICCAI community for his research on Ultrasound imaging. Purang won numerous awards and honors. Some highlights would include being the 2020 MICCAI fellow and winning the Killam faculty research prize.

Prof. Joseph Kvedar is THE expert in terms of telehealth and digital health. He is leveraging information technology, such as cell phones, computers, networked devices and remote health monitoring tools to improve care delivery.  He is a Professor of Dermatology at Harvard Medical School, and vice president of Partners healthcare. He is also the editor-in-chief of npj Digital Medicine.

Andrew Janowczyk is an assistant professor at Emory University, USA. Andrew’s research focuses on applying computer vision and machine learning algorithms to digital pathology. His key area of expertise is in leveraging deep learning to build computational models for aiding pathologists in many common tasks, such as disease detection and cancer grading. 

Robert MacDougall is the co-founder and current VP of Product and Customer Success at Quantivly. Quantivly is a start-up that is building the digital twin of radiology operations. 

Professor Rückert’s field of research is the area of Artificial Intelligence (AI) and Machine Learning and their application to medicine and healthcare. His research focuses on (1) the development of innovative algorithms for biomedical image acquisition, image analysis and image interpretation – especially in the areas of image reconstruction, registration, segmentation, tracking and modelling; (2) AI for extracting clinically useful information from biomedical images – especially for computer-assisted diagnosis and prognosis. Since 2020, Daniel Rückert is Alexander von Humboldt Professor for AI in Medicine and Healthcare at the Technical University of Munich. He is also a Professor at Imperial College London.

Federated disentangled representation learning for unsupervised brain anomaly detection

Jakob Nikolas kather is a professor at Technical University Dresden, leading the department of Clinical Artificial Intelligence at Else Kroener Fresenius Center for Digital Health. As a physician, he specializes in Internal Medicine and gastrointestinal oncology. As a researcher, he focuses on deep learning for immunotherapy biomarkers in cancer.

Swarm learning for decentralized artificial intelligence in cancer histopathology

Prateek Prasanna is an assistant professor in the Biomedical Informatics department at Stony Brook University, New York. He directs the Imaging Informatics for Precision Medicine Lab. His research interests lie at the intersection of medical image analysis and machine learning. We talked about the following papers:

1. Temporal Context Matters: Enhancing Single Image Prediction with Disease Progression Representations

2. RadioTransformer: A Cascaded Global-Focal Transformer for Visual Attention–guided Disease Classification

Michael Levin is a Distinguished Professor in the Biology at Tufts. Mike also serves as the director of the Allen Discovery Center at Tufts and the Tufts Center for Regenerative and Developmental Biology. He is a computer scientist by training, looking at some of the most fundamental questions of biology such as pattern formation, embryogenesis and regeneration.

Links to specific ideas and information

1. https://drmichaellevin.org/resources/software.html 2. https://drmichaellevin.org/resources/levinbot.html 3.  https://drmichaellevin.org/presentations/ 4. https://drmichaellevin.org/research/

Sailesh Conjeti is on a mission to bring AI-based solutions to Healthcare and translating them to clinical use to make a difference. He is the Functional Lead of Data Science at Siemens Healthineers. You can read his blogposts at https://www.saileshconjeti.com/blog.

Ismini Lourentzou is an Assistant Professor of Computer Science at Virginia Tech. Prior to VT, she spent a year as research scientist (Research Staff Member) at IBM Almaden Research Center, working on Machine Learning, Natural Language Processing and Information Retrieval problems. Her research interests are broadly defined at the intersection of Data Science, Big Data, Machine Learning, and Artificial Intelligence. 

Chest ImaGenome Dataset for Clinical Reasoning: https://openreview.net/forum?id=H-d5634yVi

Mathias Unberath is an assistant professor in the Department of Computer Science, and is affiliated with the Laboratory for Computational Sensing and Robotics and the Malone Center for Engineering in Healthcare. With his group—the Advanced Robotics and Computationally AugmenteD Environments (ARCADE) Lab—he advances healthcare by creating collaborative intelligent systems that support clinical workflows. Through synergistic research on imaging, computer vision, machine learning, and interaction design, he builds human-centered solutions that are embodied in emerging technology such as mixed reality and robotics.

Pre-print of the paper we discussed: https://arxiv.org/pdf/2112.12596v1.pdf

Taufique Joarder is a health policy and systems researcher and a university faculty. He has thirteen years of national and international experience and a doctorate in public health with expertise in health policy and systems research, teaching and training as well as extensive publishing. His background also includes higher leadership positions in NGOs/CSOs, faculty positions, policy-relevant engagements in Bangladesh and abroad, and extensive media involvement (as an expert, guest discussant, moderator, and TV anchor).