59 citations · 101 across the 9 of their papers we have counts for
7 papers · 1 filter
Constrained Deep Networks: Lagrangian Optimization via Log-Barrier Extensions
Hoel Kervadec, Jose Dolz, Jing Yuan +3
This study investigates imposing hard inequality constraints on the outputs of convolutional neural networks (CNN) during training. Several recent works showed that the theoretical…
Modern Convex Optimization to Medical Image Analysis
Jing Yuan, Aaron Fenster
Recently, diagnosis, therapy and monitoring of human diseases involve a variety of imaging modalities, such as magnetic resonance imaging(MRI), computed tomography(CT), Ultrasound(…
Isointense Infant Brain Segmentation with a Hyper-dense Connected Convolutional Neural Network
Jose Dolz, Ismail Ben Ayed, Jing Yuan +1
Neonatal brain segmentation in magnetic resonance (MR) is a challenging problem due to poor image quality and low contrast between white and gray matter regions. Most existing appr…
Shape Complexes in Continuous Max-Flow Hierarchical Multi-Labeling Problems
John S. H. Baxter, Jing Yuan, Terry M. Peters
Although topological considerations amongst multiple labels have been previously investigated in the context of continuous max-flow image segmentation, similar investigations have…
A Proximal Bregman Projection Approach to Continuous Max-Flow Problems Using Entropic Distances
John S. H. Baxter, Martin Rajchl, Jing Yuan +1
One issue limiting the adaption of large-scale multi-region segmentation is the sometimes prohibitive memory requirements. This is especially troubling considering advances in mass…
A Continuous Max-Flow Approach to Multi-Labeling Problems under Arbitrary Region Regularization
John S. H. Baxter, Martin Rajchl, Jing Yuan +1
The incorporation of region regularization into max-flow segmentation has traditionally focused on ordering and part-whole relationships. A side effect of the development of such m…
A Continuous Max-Flow Approach to General Hierarchical Multi-Labeling Problems
John S. H. Baxter, Martin Rajchl, Jing Yuan +1
Multi-region segmentation algorithms often have the onus of incorporating complex anatomical knowledge representing spatial or geometric relationships between objects, and general-…