papersSEP 10 04:00 UTC
Method reconstructs volumetric CT scans from single chest X-rays via multi-pass blended learning
Researchers propose a multi-pass, multi-view blended learning approach for generating full 3D chest CT volumes from a single 2D chest radiograph. The task is an ill-posed inverse problem, made harder by the limited availability of paired X-ray and CT training data. The paper builds on earlier methods that relied on digitally reconstructed radiographs to overcome data scarcity.