3d-reconstruction

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papersSEP 12 04:00 UTC

Calibration Audit Questions Confidence Scores in Feed-Forward 3D Reconstruction Models

A study examines whether the per-pixel confidence values produced by feed-forward 3D reconstruction models can be treated as reliable uncertainty estimates. Because these scores are trained mainly as loss weights, the authors audit how well they are calibrated for downstream use. The paper reports on the limits of reusing them as an uncertainty signal.

3d-reconstruction/uncertainty/calibration/arxiv

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.

medical-imaging/ct-synthesis/research/deep-learning