2.7k citations · 9.2k across the 86 of their papers we have counts for
6 papers · 2 filters
Trackerless freehand ultrasound with sequence modelling and auxiliary transformation over past and future frames
Qi Li, Ziyi Shen, Qian Li +5
Three-dimensional (3D) freehand ultrasound (US) reconstruction without a tracker can be advantageous over its two-dimensional or tracked counterparts in many clinical applications.…
Spatiotemporal singular value decomposition for denoising in photoacoustic imaging with low-energy excitation light source
Mengjie Shi, Tom Vercauteren, Wenfeng Xia
Photoacoustic (PA) imaging is an emerging hybrid imaging modality that combines rich optical spectroscopic contrast and high ultrasonic resolution and thus holds tremendous promise…
Fetal Brain Tissue Annotation and Segmentation Challenge Results
Kelly Payette, Hongwei Li, Priscille de Dumast +55
In-utero fetal MRI is emerging as an important tool in the diagnosis and analysis of the developing human brain. Automatic segmentation of the developing fetal brain is a vital ste…
A Dempster-Shafer approach to trustworthy AI with application to fetal brain MRI segmentation
Lucas Fidon, Michael Aertsen, Florian Kofler +18
Deep learning models for medical image segmentation can fail unexpectedly and spectacularly for pathological cases and images acquired at different centers than training images, wi…
ECONet: Efficient Convolutional Online Likelihood Network for Scribble-based Interactive Segmentation
Muhammad Asad, Lucas Fidon, Tom Vercauteren
Automatic segmentation of lung lesions associated with COVID-19 in CT images requires large amount of annotated volumes. Annotations mandate expert knowledge and are time-intensive…
CrossMoDA 2021 challenge: Benchmark of Cross-Modality Domain Adaptation techniques for Vestibular Schwannoma and Cochlea Segmentation
Reuben Dorent, Aaron Kujawa, Marina Ivory +37
Domain Adaptation (DA) has recently raised strong interests in the medical imaging community. While a large variety of DA techniques has been proposed for image segmentation, most…