Deep learning for unsupervised domain adaptation in medical imaging: Recent advancements and future perspectives
Deep learning has demonstrated remarkable performance across various tasks in medical
imaging. However, these approaches primarily focus on supervised learning, assuming that …
imaging. However, these approaches primarily focus on supervised learning, assuming that …
Data efficient deep learning for medical image analysis: A survey
The rapid evolution of deep learning has significantly advanced the field of medical image
analysis. However, despite these achievements, the further enhancement of deep learning …
analysis. However, despite these achievements, the further enhancement of deep learning …
Labrad-or: lightweight memory scene graphs for accurate bimodal reasoning in dynamic operating rooms
Modern surgeries are performed in complex and dynamic settings, including ever-changing
interactions between medical staff, patients, and equipment. The holistic modeling of the …
interactions between medical staff, patients, and equipment. The holistic modeling of the …
Evaluation of single-stage vision models for pose estimation of surgical instruments
Purpose Multiple applications in open surgical environments may benefit from adoption of
markerless computer vision depending on associated speed and accuracy requirements …
markerless computer vision depending on associated speed and accuracy requirements …
SegmentOR: Obtaining Efficient Operating Room Semantics Through Temporal Propagation
The digitization of surgical operating rooms (OR) has gained significant traction in the
scientific and medical communities. However, existing deep-learning methods for operating …
scientific and medical communities. However, existing deep-learning methods for operating …
Optimizing latent graph representations of surgical scenes for unseen domain generalization
Purpose Advances in deep learning have resulted in effective models for surgical video
analysis; however, these models often fail to generalize across medical centers due to …
analysis; however, these models often fail to generalize across medical centers due to …
Optimizing Latent Graph Representations of Surgical Scenes for Zero-Shot Domain Transfer
Purpose: Advances in deep learning have resulted in effective models for surgical video
analysis; however, these models often fail to generalize across medical centers due to …
analysis; however, these models often fail to generalize across medical centers due to …
[HTML][HTML] A human mesh-centered approach to action recognition in the operating room
B Liu, G Soenens, J Villarreal, J Jopling… - Artificial Intelligence …, 2024 - oaepublish.com
Aim: Video review programs in hospitals play a crucial role in optimizing operating room
workflows. In scenarios where split-seconds can change the outcome of a surgery, the …
workflows. In scenarios where split-seconds can change the outcome of a surgery, the …
Towards an Action Recognition Framework for Endovascular Surgery
Objective knowledge about instrument manoeuvres in endovascular surgery is essential for
evaluating surgical skills and developing advanced technologies for cathlab routines. To the …
evaluating surgical skills and developing advanced technologies for cathlab routines. To the …