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Found 12 papers, 1 papers with code
TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research
To validate the dataset's utility, 5 competitive Deep Learning models for automatic kidney segmentation were benchmarked, yielding average DICE scores from 83. 2% to 89. 1% for CT, and 61. 9% to 79. 4% for US images.
Full Contextual Attention for Multi-resolution Transformers in Semantic Segmentation
In particular, vision transformers construct compressed global representations through self-attention and learnable class tokens.
Memory transformers for full context and high-resolution 3D Medical Segmentation
Transformer models achieve state-of-the-art results for image segmentation.
StaSiS-Net: a stacked and siamese stereo network for depth reconstruction in modern 3D laparoscopy.
Accurate and real-time methodologies for a non-invasive three-dimensional representa-tion and reconstruction of internal patient structures is one of the main research fieldsin computer-assisted surgery and endoscopy.
Surgical Data Science -- from Concepts toward Clinical Translation
We further complement this technical perspective with (4) a review of currently available SDS products and the translational progress from academia and (5) a roadmap for faster clinical translation and exploitation of the full potential of SDS, based on an international multi-round Delphi process.
Deep Shape-from-Template: Wide-Baseline, Dense and Fast Registration and Deformable Reconstruction from a Single Image
Compared to previous non-DNN SfT methods, it does not involve numerical optimization at run-time, and is a dense, wide-baseline solution that does not demand, and does not suffer from, feature-based matching.
Dense Non-Rigid Structure-From-Motion and Shading With Unknown Albedos
Significant progress has been recently made in Non-Rigid Structure-from-Motion (NRSfM).
SLAM based Quasi Dense Reconstruction For Minimally Invasive Surgery Scenes
In this paper, a quasi dense reconstruction algorithm of surgical scene is proposed.
Inextensible Non-Rigid Shape-From-Motion by Second-Order Cone Programming
We show for the first time how to construct a Second-Order Cone Programming (SOCP) problem for Non-Rigid Shape-from-Motion (NRSfM) using the Maximum-Depth Heuristic (MDH).
As-Rigid-As-Possible Volumetric Shape-From-Template
Volumetric SfT uses the object's full volume to express the deformation constraints and reconstructs the object's surface and interior deformation.
Shape-From-Template in Flatland
We focus on isometric deformations, for which 2DSfT is a well-posed problem, and admits an analytical local solution which may be used to initialize nonconvex refinement.
Template-Based Isometric Deformable 3D Reconstruction with Sampling-Based Focal Length Self-Calibration
We propose (i) a general variational framework that applies to (calibrated and uncalibrated) general camera models and (ii) self-calibrating 3D reconstruction algorithms for the weak-perspective and full-perspective camera models.
