68 citations · 99 across the 14 of their papers we have counts for
14 papers
Boundary Constraint-free Biomechanical Model-Based Surface Matching for Intraoperative Liver Deformation Correction
Zixin Yang, Richard Simon, Kelly Merrell +1
In image-guided liver surgery, 3D-3D non-rigid registration methods play a crucial role in estimating the mapping between the preoperative model and the intraoperative surface repr…
Medical Vision Language Pretraining: A survey
Prashant Shrestha, Sanskar Amgain, Bidur Khanal +2
Medical Vision Language Pretraining (VLP) has recently emerged as a promising solution to the scarcity of labeled data in the medical domain. By leveraging paired/unpaired vision a…
Improving Medical Image Classification in Noisy Labels Using Only Self-supervised Pretraining
Bidur Khanal, Binod Bhattarai, Bishesh Khanal +1
Noisy labels hurt deep learning-based supervised image classification performance as the models may overfit the noise and learn corrupted feature extractors. For natural image clas…
M-VAAL: Multimodal Variational Adversarial Active Learning for Downstream Medical Image Analysis Tasks
Bidur Khanal, Binod Bhattarai, Bishesh Khanal +2
Acquiring properly annotated data is expensive in the medical field as it requires experts, time-consuming protocols, and rigorous validation. Active learning attempts to minimize…
A Disparity Refinement Framework for Learning-based Stereo Matching Methods in Cross-domain Setting for Laparoscopic Images
Zixin Yang, Richard Simon, Cristian A. Linte
Purpose: Stereo matching methods that enable depth estimation are crucial for visualization enhancement applications in computer-assisted surgery (CAS). Learning-based stereo match…
Learning Feature Descriptors for Pre- and Intra-operative Point Cloud Matching for Laparoscopic Liver Registration
Zixin Yang, Richard Simon, Cristian A. Linte
Purpose: In laparoscopic liver surgery (LLS), pre-operative information can be overlaid onto the intra-operative scene by registering a 3D pre-operative model to the intra-operativ…