Relational Reasoning Network (RRN) for Anatomical Landmarking

no code implementations • 8 Apr 2019 • Neslisah Torosdagli, Syed Anwar, Payal Verma, Denise K Liberton, Janice S. Lee, Wade W. Han, Ulas Bagci

Purpose: We perform anatomical landmarking for craniomaxillofacial (CMF) bones without explicitly segmenting them.

Imputation Informativeness +2

Deep Geodesic Learning for Segmentation and Anatomical Landmarking

no code implementations • 6 Oct 2018 • Neslisah Torosdagli, Denise K. Liberton, Payal Verma, Murat Sincan, Janice S. Lee, Ulas Bagci

Specifically, we focus on the challenging problem of mandible segmentation from cone-beam computed tomography (CBCT) scans and identification of 9 anatomical landmarks of the mandible on the geodesic space.

Anatomy Data Augmentation +3

Robust and fully automated segmentation of mandible from CT scans

no code implementations • 23 Feb 2017 • Neslisah Torosdagli, Denise K. Liberton, Payal Verma, Murat Sincan Janice Lee, Sumanta Pattanaik, Ulas Bagci

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.

Computed Tomography (CT) Image Segmentation +2