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Deep Learning Applications for Histological Image Analysis

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  • UserMatej Halinkovic, Vision and Graphics Group, Institute of Computer Engineering and Applied Informatics, Slovak University of Technology
  • ClockTuesday 26 September 2023, 11:00-12:00
  • HouseOnline event - Zoom link in the description.

If you have a question about this talk, please contact Ines Machado.

The Cancer Research UK Cambridge Centre and the Department of Radiology at Addenbrooke’s are pleased to announce a seminar series on Artificial Intelligence (AI) in Medicine, which aims to provide a comprehensive overview of the latest developments in this rapidly evolving field. As AI continues to revolutionize healthcare, we believe it is essential to explore its potential and discuss the challenges and opportunities it presents.

The seminar series will feature prominent experts in the field who will share their research and insights on a range of topics, including AI applications in disease diagnosis, drug discovery, and patient care. Each seminar will also include a Q&A session to facilitate discussion and exchange of ideas among participants.

The next seminar will be held on the 26th of September 2023 at 11am (Online, Zoom) and will feature:

Deep Learning Applications for Histological Image Analysis – Matej Halinkovic, Vision and Graphics Group, Institute of Computer Engineering and Applied Informatics, Slovak University of Technology.

Analysis of structures contained in tissue samples and the relevant contextual information is of utmost importance to histopathologists during diagnosis. Our work primarily focuses on histological tissue samples and helping pathologists with the analysis of cardiac biopsies. We propose a method that provides supporting information in the form of structure segmentation to histopathologists while simulating their workflows. The proposed method utilizes semantic nuclei maps in addition to hierarchical image input for the semantic segmentation of blood vessels, inflammation, and endocardium in heart tissue. We demonstrate that the decision process of the deep learning model utilizes the supporting information correctly through custom-designed attention modules.

Matej is a Ph.D. at the Slovak University of Technology in Bratislava focusing on explainable deep learning methods for computer vision. Matej has worked on research projects that centered on medical applications of computer vision and toxicology. He graduated magna cum laude and received the rector’s prize for his master’s thesis. Professionally, he’s also experienced with applications of computer vision in satellite imagery; working on projects supported by the European Space Agency.

Each session will involve two talks, followed by an interactive discussion with coffee and pastries! We hope that this seminar series will be a valuable platform for researchers, practitioners, and students to learn about the latest trends and explore collaborations in the exciting field of AI in Medicine.

This is a hybrid event so you can also join via Zoom:

Meeting ID: 990 5046 7573 and Passcode: 617729

We look forward to your participation! If you are interested in getting involved and presenting your work, please email Ines Machado at

This talk is part of the Cambridge MedAI Seminar Series series.

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