2.7k citations · 5.1k across the 61 of their papers we have counts for
85 papers
An unsupervised learning-based shear wave tracking method for ultrasound elastography
Remi Delaunay, Yipeng Hu, Tom Vercauteren
Shear wave elastography involves applying a non-invasive acoustic radiation force to the tissue and imaging the induced deformation to infer its mechanical properties. This work in…
UPL-SFDA: Uncertainty-aware Pseudo Label Guided Source-Free Domain Adaptation for Medical Image Segmentation
Jianghao Wu, Guotai Wang, Ran Gu +6
Domain Adaptation (DA) is important for deep learning-based medical image segmentation models to deal with testing images from a new target domain. As the source-domain data are us…
Unified Brain MR-Ultrasound Synthesis using Multi-Modal Hierarchical Representations
Reuben Dorent, Nazim Haouchine, Fryderyk Kögl +9
We introduce MHVAE, a deep hierarchical variational auto-encoder (VAE) that synthesizes missing images from various modalities. Extending multi-modal VAEs with a hierarchical laten…
DEEPBEAS3D: Deep Learning and B-Spline Explicit Active Surfaces
Helena Williams, João Pedrosa, Muhammad Asad +4
Deep learning-based automatic segmentation methods have become state-of-the-art. However, they are often not robust enough for direct clinical application, as domain shifts between…
Privileged Anatomical and Protocol Discrimination in Trackerless 3D Ultrasound Reconstruction
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without using any additional external tracking device has seen recent advances with deep neural networks (DNNs). In t…
MedShapeNet -- A Large-Scale Dataset of 3D Medical Shapes for Computer Vision
Jianning Li, Zongwei Zhou, Jiancheng Yang +154
Prior to the deep learning era, shape was commonly used to describe the objects. Nowadays, state-of-the-art (SOTA) algorithms in medical imaging are predominantly diverging from co…