activity
20162024
most citedSurgical Data Science: Enabling Next-Generation Surgery

578 citations · 3k across the 77 of their papers we have counts for

collaborators

83 papers

cs.CV2024★ 11 cited

SAR-RARP50: Segmentation of surgical instrumentation and Action Recognition on Robot-Assisted Radical Prostatectomy Challenge

Dimitrios Psychogyios, Emanuele Colleoni, Beatrice Van Amsterdam +47

Surgical tool segmentation and action recognition are fundamental building blocks in many computer-assisted intervention applications, ranging from surgical skills assessment to de…

eess.IV2023★ 9 cited

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…

cs.CV2023★ 25 cited

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…

eess.IV2023

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…

cs.CV2023★ 1 cited

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…

eess.IV2023

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…

cs.CV2023

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…

cs.RO2023

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…

cs.CV2023★ 6 cited

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…

cs.CV2023★ 2 cited

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…

cs.RO2023★ 1 cited

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…

cs.CV2023★ 3 cited

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…

cs.RO2023★ 9 cited

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…

cs.CV2023★ 6 cited

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…

cs.CV2022

Objective Surgical Skills Assessment and Tool Localization: Results from the MICCAI 2021 SimSurgSkill Challenge

Aneeq Zia, Kiran Bhattacharyya, Xi Liu +12

Timely and effective feedback within surgical training plays a critical role in developing the skills required to perform safe and efficient surgery. Feedback from expert surgeons,…

cs.CV2022

Generalized Product-of-Experts for Learning Multimodal Representations in Noisy Environments

Abhinav Joshi, Naman Gupta, Jinang Shah +3

A real-world application or setting involves interaction between different modalities (e.g., video, speech, text). In order to process the multimodal information automatically and…

cs.CV2022★ 2 cited

Retrieval of surgical phase transitions using reinforcement learning

Yitong Zhang, Sophia Bano, Ann-Sophie Page +3

In minimally invasive surgery, surgical workflow segmentation from video analysis is a well studied topic. The conventional approach defines it as a multi-class classification prob…

eess.IV2022

Learning-Based Keypoint Registration for Fetoscopic Mosaicking

Alessandro Casella, Sophia Bano, Francisco Vasconcelos +7

In Twin-to-Twin Transfusion Syndrome (TTTS), abnormal vascular anastomoses in the monochorionic placenta can produce uneven blood flow between the two fetuses. In the current pract…

eess.IV2022

Fluorescence angiography classification in colorectal surgery -- A preliminary report

Antonio S Soares, Sophia Bano, Neil T Clancy +3

Background: Fluorescence angiography has shown very promising results in reducing anastomotic leaks by allowing the surgeon to select optimally perfused tissue. However, subjective…

eess.IV2022

Placental Vessel Segmentation and Registration in Fetoscopy: Literature Review and MICCAI FetReg2021 Challenge Findings

Sophia Bano, Alessandro Casella, Francisco Vasconcelos +28

Fetoscopy laser photocoagulation is a widely adopted procedure for treating Twin-to-Twin Transfusion Syndrome (TTTS). The procedure involves photocoagulation pathological anastomos…

cs.CV2022★ 2 cited

Task-Aware Active Learning for Endoscopic Image Analysis

Shrawan Kumar Thapa, Pranav Poudel, Binod Bhattarai +1

Semantic segmentation of polyps and depth estimation are two important research problems in endoscopic image analysis. One of the main obstacles to conduct research on these resear…

eess.IV2022★ 3 cited

Histogram of Oriented Gradients Meet Deep Learning: A Novel Multi-task Deep Network for Medical Image Semantic Segmentation

Binod Bhattarai, Ronast Subedi, Rebati Raman Gaire +2

We present our novel deep multi-task learning method for medical image segmentation. Existing multi-task methods demand ground truth annotations for both the primary and auxiliary…

cs.CV2022★ 39 cited

Bimodal Camera Pose Prediction for Endoscopy

Anita Rau, Binod Bhattarai, Lourdes Agapito +1

Deducing the 3D structure of endoscopic scenes from images is exceedingly challenging. In addition to deformation and view-dependent lighting, tubular structures like the colon pre…

cs.CV2022★ 78 cited

CholecTriplet2021: A benchmark challenge for surgical action triplet recognition

Chinedu Innocent Nwoye, Deepak Alapatt, Tong Yu +59

Context-aware decision support in the operating room can foster surgical safety and efficiency by leveraging real-time feedback from surgical workflow analysis. Most existing works…