2 citations · 3 across the 5 of their papers we have counts for
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cs.CV2019
Extracting 2D weak labels from volume labels using multiple instance learning in CT hemorrhage detection
Samuel W. Remedios, Zihao Wu, Camilo Bermudez +6
Multiple instance learning (MIL) is a supervised learning methodology that aims to allow models to learn instance class labels from bag class labels, where a bag is defined to cont…
cs.CV2019
Distributed deep learning for robust multi-site segmentation of CT imaging after traumatic brain injury
Samuel Remedios, Snehashis Roy, Justin Blaber +6
Machine learning models are becoming commonplace in the domain of medical imaging, and with these methods comes an ever-increasing need for more data. However, to preserve patient…