activity
20182021
most citedSelf-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images

4 citations · 5 across the 2 of their papers we have counts for

collaborators

5 papers

eess.IV20214 cited

Self-Supervised Generative Adversarial Network for Depth Estimation in Laparoscopic Images

Baoru Huang, Jianqing Zheng, Anh Nguyen +4

Dense depth estimation and 3D reconstruction of a surgical scene are crucial steps in computer assisted surgery. Recent work has shown that depth estimation from a stereo images pa…

cs.CV20211 cited

H-Net: Unsupervised Attention-based Stereo Depth Estimation Leveraging Epipolar Geometry

Baoru Huang, Jian-Qing Zheng, Stamatia Giannarou +1

Depth estimation from a stereo image pair has become one of the most explored applications in computer vision, with most of the previous methods relying on fully supervised learnin…

cs.CY2020

Surgical Data Science -- from Concepts toward Clinical Translation

Lena Maier-Hein, Matthias Eisenmann, Duygu Sarikaya +47

Recent developments in data science in general and machine learning in particular have transformed the way experts envision the future of surgery. Surgical Data Science (SDS) is a…

cs.RO2020

Autonomous Tissue Scanning under Free-Form Motion for Intraoperative Tissue Characterisation

Jian Zhan, Joao Cartucho, Stamatia Giannarou

In Minimally Invasive Surgery (MIS), tissue scanning with imaging probes is required for subsurface visualisation to characterise the state of the tissue. However, scanning of larg…

cs.CY2018

Surgical Data Science: A Consensus Perspective

Lena Maier-Hein, Matthias Eisenmann, Carolin Feldmann +25

Surgical data science is a scientific discipline with the objective of improving the quality of interventional healthcare and its value through capturing, organization, analysis, a…