578 citations · 3k across the 77 of their papers we have counts for
13 papers · 1 filter
Latent Disentanglement in Mesh Variational Autoencoders Improves the Diagnosis of Craniofacial Syndromes and Aids Surgical Planning
Simone Foti, Alexander J. Rickart, Bongjin Koo +9
The use of deep learning to undertake shape analysis of the complexities of the human head holds great promise. However, there have traditionally been a number of barriers to accur…
SimCol3D -- 3D Reconstruction during Colonoscopy Challenge
Anita Rau, Sophia Bano, Yueming Jin +19
Colorectal cancer is one of the most common cancers in the world. While colonoscopy is an effective screening technique, navigating an endoscope through the colon to detect polyps…
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 spatio-temporal network for video semantic segmentation in surgical videos
Maria Grammatikopoulou, Ricardo Sanchez-Matilla, Felix Bragman +5
Semantic segmentation in surgical videos has applications in intra-operative guidance, post-operative analytics and surgical education. Segmentation models need to provide accurate…
Self-Knowledge Distillation for Surgical Phase Recognition
Jinglu Zhang, Santiago Barbarisi, Abdolrahim Kadkhodamohammadi +2
Purpose: Advances in surgical phase recognition are generally led by training deeper networks. Rather than going further with a more complex solution, we believe that current model…
A Client-server Deep Federated Learning for Cross-domain Surgical Image Segmentation
Ronast Subedi, Rebati Raman Gaire, Sharib Ali +3
This paper presents a solution to the cross-domain adaptation problem for 2D surgical image segmentation, explicitly considering the privacy protection of distributed datasets belo…
Online estimation of the hand-eye transformation from surgical scenes
Krittin Pachtrachai, Francisco Vasconcelos, Danail Stoyanov
Hand-eye calibration algorithms are mature and provide accurate transformation estimations for an effective camera-robot link but rely on a sufficiently wide range of calibration d…
3D Generative Model Latent Disentanglement via Local Eigenprojection
Simone Foti, Bongjin Koo, Danail Stoyanov +1
Designing realistic digital humans is extremely complex. Most data-driven generative models used to simplify the creation of their underlying geometric shape do not offer control o…
Shifted-Windows Transformers for the Detection of Cerebral Aneurysms in Microsurgery
Jinfan Zhou, William Muirhead, Simon C. Williams +3
Purpose: Microsurgical Aneurysm Clipping Surgery (MACS) carries a high risk for intraoperative aneurysm rupture. Automated recognition of instances when the aneurysm is exposed in…
Local Path Planning among Pushable Objects based on Reinforcement Learning
Linghong Yao, Valerio Modugno, Andromachi Maria Delfaki +3
In this paper, we introduce a method to deal with the problem of robot local path planning among pushable objects -- an open problem in robotics. In particular, we achieve that by…
MoBYv2AL: Self-supervised Active Learning for Image Classification
Razvan Caramalau, Binod Bhattarai, Danail Stoyanov +1
Active learning(AL) has recently gained popularity for deep learning(DL) models. This is due to efficient and informative sampling, especially when the learner requires large-scale…
Deep Reinforcement Learning for Concentric Tube Robot Path Following
Keshav Iyengar, Sarah Spurgeon, Danail Stoyanov
As surgical interventions trend towards minimally invasive approaches, Concentric Tube Robots (CTRs) have been explored for various interventions such as brain, eye, fetoscopic, lu…
Ultrasound Plane Pose Regression: Assessing Generalized Pose Coordinates in the Fetal Brain
Chiara Di Vece, Maela Le Lous, Brian Dromey +4
In obstetric ultrasound (US) scanning, the learner's ability to mentally build a three-dimensional (3D) map of the fetus from a two-dimensional (2D) US image represents a significa…