AI RESEARCH
Statistical Hand Shape Modeling from Clinical CT Scans Using Deep Learning and Implicit Skinning
arXiv CS.CV
•
ArXi:2605.16980v1 Announce Type: new Accurate segmentation and statistical shape modeling of hand anatomy have significant implications for medical diagnostics, ergonomics, and biomechanics. This study proposes an AI-assisted reconstruction pipeline for segmenting and analyzing hand anatomy from 1,271 elbow-to-hand (e2h-CT) computed tomography scans. A Pix2Pix-based conditional generative adversarial network is first employed to remove plaster cast and background artifacts from CT volumes.