COIN: Counterfactual inpainting for weakly supervised semantic segmentation for medical images

arXiv:2404.12832v1 Announce Type: cross
Abstract: Deep learning is dramatically transforming the field of medical imaging and radiology, enabling the identification of pathologies in medical images, including computed tomography (CT) and X-ray scans. However, the performance of deep learning models, particularly in segmentation tasks, is often limited by the need for extensive annotated datasets. To address this challenge, the capabilities of weakly supervised semantic segmentation are explored through the lens of Explainable AI and the generation of counterfactual explanations. The scope …

abstract arxiv counterfactual cs.ai cs.cv cs.lg deep learning enabling however identification images imaging inpainting medical medical imaging performance radiology ray scans segmentation semantic tasks type x-ray