Publications (4)
Sequential 3D U-Nets for Biologically-Informed Brain Tumor Segmentation
Andrew Beers, Ken Chang, James Brown +5
Deep learning has quickly become the weapon of choice for brain lesion segmentation. However, few existing algorithms pre-configure any biological context of their chosen segmentat…
Deep Learning-based Prediction of Breast Cancer Tumor and Immune Phenotypes from Histopathology
Tiago Gonçalves, Dagoberto Pulido-Arias, Julian Willett +8
The interactions between tumor cells and the tumor microenvironment (TME) dictate therapeutic efficacy of radiation and many systemic therapies in breast cancer. However, to date,…
Identifying the Best Machine Learning Algorithms for Brain Tumor Segmentation, Progression Assessment, and Overall Survival Prediction in the BRATS Challenge
Spyridon Bakas, Mauricio Reyes, Andras Jakab +421
Gliomas are the most common primary brain malignancies, with different degrees of aggressiveness, variable prognosis and various heterogeneous histologic sub-regions, i.e., peritum…
DeepNeuro: an open-source deep learning toolbox for neuroimaging
Andrew Beers, James Brown, Ken Chang +4
Translating neural networks from theory to clinical practice has unique challenges, specifically in the field of neuroimaging. In this paper, we present DeepNeuro, a deep learning…