53 citations · 134 across the 13 of their papers we have counts for
4 papers · 1 filter
SegViz: A federated-learning based framework for multi-organ segmentation on heterogeneous data sets with partial annotations
Adway U. Kanhere, Pranav Kulkarni, Paul H. Yi +1
Segmentation is one of the most primary tasks in deep learning for medical imaging, owing to its multiple downstream clinical applications. However, generating manual annotations f…
Radiomic Synthesis Using Deep Convolutional Neural Networks
Vishwa S. Parekh, Michael A. Jacobs
Radiomics is a rapidly growing field that deals with modeling the textural information present in the different tissues of interest for clinical decision support. However, the proc…
MPRAD: A Multiparametric Radiomics Framework
Vishwa S. Parekh, Michael A. Jacobs
Multiparametric radiological imaging is vital for detection, characterization and diagnosis of many different diseases. The use of radiomics for quantitative extraction of textural…
Unsupervised Non Linear Dimensionality Reduction Machine Learning methods applied to Multiparametric MRI in cerebral ischemia: Preliminary Results
Vishwa S. Parekh, Jeremy R. Jacobs, Michael A. Jacobs
The evaluation and treatment of acute cerebral ischemia requires a technique that can determine the total area of tissue at risk for infarction using diagnostic magnetic resonance…