You are warmly invited to the next PRG Seminar.

Date & Time: Monday 06/10/2025 14:00-14:40

Location: JC 1.33A

Speaker: David Morrison

Title: Synthetic Whole Slide Image Patch Embeddings for Multiple Instance Learning

Abstract: Obtaining high-quality data is a persistent challenge for the training of computational pathology models. As medical data, Whole-slide images (WSIs) are often held under restrictive terms by medical institutions and, as a result, are hard to access by researchers. Where data is available, the number of whole slide images can be limited and skewed towards common pathology types. In addition, there can be issues with labelling: slide-level labels may lack information about specific pathologies, for example, they may be limited to binary labels of normal or malignant, while annotations at the level of patches are rarely available.

Synthetic data generation is a possible solution to these problems by allowing researchers to produce data on demand that can be used in an unrestricted manner with high-quality labels. I have previously presented on the generation of synthetic patch data. In this talk, I will discuss an extension to this work in which this approach is combined with models trained to characterise the slide as a whole in order to provide a synthesis process for data for use with multiple instance learning techniques, commonly used in whole slide image classification.

We hope you can join us!