49 citations · 138 across the 10 of their papers we have counts for
8 papers · 1 filter
Deep-COVID: Predicting COVID-19 From Chest X-Ray Images Using Deep Transfer Learning
Shervin Minaee, Rahele Kafieh, Milan Sonka +2
The COVID-19 pandemic is causing a major outbreak in more than 150 countries around the world, having a severe impact on the health and life of many people globally. One of the cru…
DeepCenterline: a Multi-task Fully Convolutional Network for Centerline Extraction
Zhihui Guo, Junjie Bai, Yi Lu +5
A novel centerline extraction framework is reported which combines an end-to-end trainable multi-task fully convolutional network (FCN) with a minimal path extractor. The FCN simul…
Just-Enough Interaction Approach to Knee MRI Segmentation: Data from the Osteoarthritis Initiative
Satyananda Kashyap, Honghai Zhang, Milan Sonka
State-of-the-art automated segmentation algorithms are not 100\% accurate especially when segmenting difficult to interpret datasets like those with severe osteoarthritis (OA). We…
Automated Segmentation of Knee MRI Using Hierarchical Classifiers and Just Enough Interaction Based Learning: Data from Osteoarthritis Initiative
Satyananda Kashyap, Ipek Oguz, Honghai Zhang +1
We present a fully automated learning-based approach for segmenting knee cartilage in the presence of osteoarthritis (OA). The algorithm employs a hierarchical set of two random fo…
Learning-Based Cost Functions for 3D and 4D Multi-Surface Multi-Object Segmentation of Knee MRI: Data from the Osteoarthritis Initiative
Satyananda Kashyap, Honghai Zhang, Karan Rao +1
A fully automated knee MRI segmentation method to study osteoarthritis (OA) was developed using a novel hierarchical set of random forests (RF) classifiers to learn the appearance…
Deep LOGISMOS: Deep Learning Graph-based 3D Segmentation of Pancreatic Tumors on CT scans
Zhihui Guo, Ling Zhang, Le Lu +4
This paper reports Deep LOGISMOS approach to 3D tumor segmentation by incorporating boundary information derived from deep contextual learning to LOGISMOS - layered optimal graph i…