163 citations · 384 across the 17 of their papers we have counts for
19 papers
Tracking Intermittent Particles with Self-Learned Visual Features
Raphael Reme, Victor Piriou, Alison Hanson +5
In time-lapse fluorescence imaging, single-particle-tracking is a powerful tool to monitor the dynamics of objects of interest, and extract information about biological processes.…
Robust Quantification of Percent Emphysema on CT via Domain Attention: the Multi-Ethnic Study of Atherosclerosis (MESA) Lung Study
Xuzhe Zhang, Elsa D. Angelini, Eric A. Hoffman +4
Robust quantification of pulmonary emphysema on computed tomography (CT) remains challenging for large-scale research studies that involve scans from different scanner types and fo…
Scribble-based fast weak-supervision and interactive corrections for segmenting whole slide images
Antoine Habis, Roy Rosman Nathanson, Vannary Meas-Yedid +2
This paper proposes a dynamic interactive and weakly supervised segmentation method with minimal user interactions to address two major challenges in the segmentation of whole slid…
Cardiac Adipose Tissue Segmentation via Image-Level Annotations
Ziyi Huang, Yu Gan, Theresa Lye +5
Automatically identifying the structural substrates underlying cardiac abnormalities can potentially provide real-time guidance for interventional procedures. With the knowledge of…
QU-BraTS: MICCAI BraTS 2020 Challenge on Quantifying Uncertainty in Brain Tumor Segmentation - Analysis of Ranking Scores and Benchmarking Results
Raghav Mehta, Angelos Filos, Ujjwal Baid +89
Deep learning (DL) models have provided state-of-the-art performance in various medical imaging benchmarking challenges, including the Brain Tumor Segmentation (BraTS) challenges.…
Recursive Refinement Network for Deformable Lung Registration between Exhale and Inhale CT Scans
Xinzi He, Jia Guo, Xuzhe Zhang +9
Unsupervised learning-based medical image registration approaches have witnessed rapid development in recent years. We propose to revisit a commonly ignored while simple and well-e…