Adam Klimont and Tomasz Bartczak present “Beyond Medical Image Segmentation. The Road Towards Cinical Insights” at the PyData London 2022 conference.
Recent progress in deep learning for medical imaging has led to impressive results. Among them is a fully automatic human organ segmentation from Computed Tomography (CT) scans. Organ segmentation can be the end goal in itself, e.g. when it is directly viewed by clinical teams. It can also serve as an input to diagnostic aid tools. Moreover, specific knowledge can be extracted out of segmentations to build databases. These databases can then be used for reasoning about the anatomy or planning treatment.
In this talk, Klimont and Bartczak describe a multi-stage pipeline for processing CT scans for abdominal aortic aneurysm (AAA) treatment planning. They share their experience in sub-organ multilabel segmentation. Klimont and Bartzak discuss the challenges with common loss functions, and with metrics not being well aligned with clinical significance. The pair will show how enhanced segmentation can be used to represent patient anatomy in an accessible way for end-users who plan treatment for new patients.