3 citations · 3 across the 1 of their papers we have counts for
2 papers
cs.CV2018
Deep Geodesic Learning for Segmentation and Anatomical Landmarking
Neslisah Torosdagli, Denise K. Liberton, Payal Verma +3
In this paper, we propose a novel deep learning framework for anatomy segmentation and automatic landmark- ing. Specifically, we focus on the challenging problem of mandible segmen…
cs.CV2017★ 3 cited
Robust and fully automated segmentation of mandible from CT scans
Neslisah Torosdagli, Denise K. Liberton, Payal Verma +3
Mandible bone segmentation from computed tomography (CT) scans is challenging due to mandible's structural irregularities, complex shape patterns, and lack of contrast in joints. F…