58 citations · 212 across the 44 of their papers we have counts for
18 papers · 1 filter
ToolTipNet: A Segmentation-Driven Deep Learning Baseline for Surgical Instrument Tip Detection
Zijian Wu, Shuojue Yang, Yueming Jin +1
In robot-assisted laparoscopic radical prostatectomy (RALP), the location of the instrument tip is important to register the ultrasound frame with the laparoscopic camera frame. A…
Point Tracking in Surgery--The 2024 Surgical Tattoos in Infrared (STIR) Challenge
Adam Schmidt, Mert Asim Karaoglu, Soham Sinha +37
Understanding tissue motion in surgery is crucial to enable applications in downstream tasks such as segmentation, 3D reconstruction, virtual tissue landmarking, autonomous probe-b…
Instrument-Splatting: Controllable Photorealistic Reconstruction of Surgical Instruments Using Gaussian Splatting
Shuojue Yang, Zijian Wu, Mingxuan Hong +4
Real2Sim is becoming increasingly important with the rapid development of surgical artificial intelligence (AI) and autonomy. In this work, we propose a novel Real2Sim methodology,…
SemICP: Semantic Non-Rigid Point Cloud Registration with Elastic Energy Regularization
Wanwen Chen, Qi Zeng, Carson Studders +6
Purpose: Accurate point cloud registration is essential in computer-aided interventions (CAI) to align multi-modal medical images for intraoperative guidance. Classical methods, su…
Image Retrieval with Intra-Sweep Representation Learning for Neck Ultrasound Scanning Guidance
Wanwen Chen, Adam Schmidt, Eitan Prisman +1
Purpose: Intraoperative ultrasound (US) can enhance real-time visualization in transoral robotic surgery. The surgeon creates a mental map with a pre-operative scan. Then, a surgic…
A-MFST: Adaptive Multi-Flow Sparse Tracker for Real-Time Tissue Tracking Under Occlusion
Yuxin Chen, Zijian Wu, Adam Schmidt +1
Purpose: Tissue tracking is critical for downstream tasks in robot-assisted surgery. The Sparse Efficient Neural Depth and Deformation (SENDD) model has previously demonstrated acc…
SegSTRONG-C: Segmenting Surgical Tools Robustly On Non-adversarial Generated Corruptions -- An EndoVis'24 Challenge
Hao Ding, Yuqian Zhang, Tuxun Lu +39
Surgical data science has seen rapid advancement with the excellent performance of end-to-end deep neural networks (DNNs). Despite their successes, DNNs have been proven susceptibl…
Augmenting Efficient Real-time Surgical Instrument Segmentation in Video with Point Tracking and Segment Anything
Zijian Wu, Adam Schmidt, Peter Kazanzides +1
The Segment Anything Model (SAM) is a powerful vision foundation model that is revolutionizing the traditional paradigm of segmentation. Despite this, a reliance on prompting each…
PIPsUS: Self-Supervised Point Tracking in Ultrasound
Wanwen Chen, Adam Schmidt, Eitan Prisman +1
Finding point-level correspondences is a fundamental problem in ultrasound (US), since it can enable US landmark tracking for intraoperative image guidance in different surgeries,…
Tracking and Mapping in Medical Computer Vision: A Review
Adam Schmidt, Omid Mohareri, Simon DiMaio +2
As computer vision algorithms increase in capability, their applications in clinical systems will become more pervasive. These applications include: diagnostics, such as colonoscop…
Surgical Tattoos in Infrared: A Dataset for Quantifying Tissue Tracking and Mapping
Adam Schmidt, Omid Mohareri, Simon DiMaio +1
Quantifying performance of methods for tracking and mapping tissue in endoscopic environments is essential for enabling image guidance and automation of medical interventions and s…
SENDD: Sparse Efficient Neural Depth and Deformation for Tissue Tracking
Adam Schmidt, Omid Mohareri, Simon DiMaio +1
Deformable tracking and real-time estimation of 3D tissue motion is essential to enable automation and image guidance applications in robotically assisted surgery. Our model, Spars…
Multi-Scale Relational Graph Convolutional Network for Multiple Instance Learning in Histopathology Images
Roozbeh Bazargani, Ladan Fazli, Larry Goldenberg +3
Graph convolutional neural networks have shown significant potential in natural and histopathology images. However, their use has only been studied in a single magnification or mul…
ResNet Structure Simplification with the Convolutional Kernel Redundancy Measure
Hongzhi Zhu, Robert Rohling, Septimiu Salcudean
Deep learning, especially convolutional neural networks, has triggered accelerated advancements in computer vision, bringing changes into our daily practice. Furthermore, the stand…
Generalizable Neural Radiance Fields for Novel View Synthesis with Transformer
Dan Wang, Xinrui Cui, Septimiu Salcudean +1
We propose a Transformer-based NeRF (TransNeRF) to learn a generic neural radiance field conditioned on observed-view images for the novel view synthesis task. By contrast, existin…
Multi-view 3D Reconstruction with Transformer
Dan Wang, Xinrui Cui, Xun Chen +5
Deep CNN-based methods have so far achieved the state of the art results in multi-view 3D object reconstruction. Despite the considerable progress, the two core modules of these me…
Rapid treatment planning for low-dose-rate prostate brachytherapy with TP-GAN
Tajwar Abrar Aleef, Ingrid T. Spadinger, Michael D. Peacock +2
Treatment planning in low-dose-rate prostate brachytherapy (LDR-PB) aims to produce arrangement of implantable radioactive seeds that deliver a minimum prescribed dose to the prost…
Co-Generation and Segmentation for Generalized Surgical Instrument Segmentation on Unlabelled Data
Megha Kalia, Tajwar Abrar Aleef, Nassir Navab +1
Surgical instrument segmentation for robot-assisted surgery is needed for accurate instrument tracking and augmented reality overlays. Therefore, the topic has been the subject of…