110 citations · 208 across the 7 of their papers we have counts for
4 papers · 1 filter
C3VDv2 -- Colonoscopy 3D video dataset with enhanced realism
Mayank V. Golhar, Lucas Sebastian Galeano Fretes, Loren Ayers +3
Spatial computer vision techniques have the potential to improve the diagnostic performance of colonoscopy. However, the lack of 3D colonoscopy datasets for training and validation…
Multi-contrast laser endoscopy for in vivo gastrointestinal imaging
Taylor L. Bobrow, Mayank Golhar, Suchapa Arayakarnkul +3
White light endoscopy is the clinical gold standard for detecting diseases in the gastrointestinal tract. Most applications involve identifying visual abnormalities in tissue color…
GAN Inversion for Data Augmentation to Improve Colonoscopy Lesion Classification
Mayank Golhar, Taylor L. Bobrow, Saowanee Ngamruengphong +1
A major challenge in applying deep learning to medical imaging is the paucity of annotated data. This study demonstrates that synthetic colonoscopy images generated by Generative A…
SLAM Endoscopy enhanced by adversarial depth prediction
Richard J. Chen, Taylor L. Bobrow, Thomas Athey +2
Medical endoscopy remains a challenging application for simultaneous localization and mapping (SLAM) due to the sparsity of image features and size constraints that prevent direct…