medical-9

Landmark Tracking

3260 papers • 126 benchmarks • 313 datasets

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Benchmarks

These leaderboards are used to track progress in landmark-tracking-18

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Libraries

i

Use these libraries to find landmark-tracking-18 models and implementations

Datasets

MBW - Zoo Dataset

Subtasks

Muscle Tendon Junction Identification

Most implemented papers

DeepTag: An Unsupervised Deep Learning Method for Motion Tracking on Cardiac Tagging Magnetic Resonance Images

Dimitris N. Metaxas, Mikael Kanski, D. Yang, Qi Chang, Zhennan Yan, Qiaoying Huang, L. Axel•Wed Mar 03 2021

This paper proposes a novel deep learning-based fully unsupervised method for in vivo motion tracking on t-MRI images and shows that this method is superior to conventional motion tracking methods in terms of landmark tracking accuracy and inference efficiency.

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Breaking Shortcut: Exploring Fully Convolutional Cycle-Consistency for Video Correspondence Learning

Philip H. S. Torr, Han Hu, Yue Cao, Zheng Zhang, Zhenda Xie, Yansong Tang, Zhenyu Jiang•Tue May 11 2021

This paper studies the underline reason behind fully convolutional training results in model collapse, indicating that the absolute positions of pixels provide a shortcut to easily accomplish cycle-consistence, which hinders the learning of meaningful visual representations.

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Reasoning structural relation for occlusion-robust facial landmark localization

Congcong Zhu, Xiaoqiang Li, Jide Li, Songmin Dai, Weiqin Tong•Sat Dec 18 2021

A structural relation network (SRN) for occlusion-robust landmark localization that aims to capture the structural relations among different facial components and achieves outstanding performance on occluded and masked faces.

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WarpPINN: Cine-MR image registration with physics-informed neural networks

Pablo Arratia L'opez, Hernán Mella, S. Uribe, D. Hurtado, F. S. Costabal•Mon Nov 21 2022

WarpPINN is introduced, a physics-informed neural network to perform image registration to obtain local metrics of heart deformation and provides precise measurements of local cardiac deformations that can be used for a better diagnosis of heart failure and for general image registration tasks.

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Paper Graph

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