386 citations · 416 across the 4 of their papers we have counts for
4 papers
Simulation-to-Real domain adaptation with teacher-student learning for endoscopic instrument segmentation
Manish Sahu, Anirban Mukhopadhyay, Stefan Zachow
Purpose: Segmentation of surgical instruments in endoscopic videos is essential for automated surgical scene understanding and process modeling. However, relying on fully supervise…
Endo-Sim2Real: Consistency learning-based domain adaptation for instrument segmentation
Manish Sahu, Ronja Strömsdörfer, Anirban Mukhopadhyay +1
Surgical tool segmentation in endoscopic videos is an important component of computer assisted interventions systems. Recent success of image-based solutions using fully-supervised…
VerSe: A Vertebrae Labelling and Segmentation Benchmark for Multi-detector CT Images
Anjany Sekuboyina, Malek E. Husseini, Amirhossein Bayat +66
Vertebral labelling and segmentation are two fundamental tasks in an automated spine processing pipeline. Reliable and accurate processing of spine images is expected to benefit cl…
Tool and Phase recognition using contextual CNN features
Manish Sahu, Anirban Mukhopadhyay, Angelika Szengel +1
A transfer learning method for generating features suitable for surgical tools and phase recognition from the ImageNet classification features [1] is proposed here. In addition, me…