1 citations · 2 across the 4 of their papers we have counts for
4 papers
Applications of Sequential Learning for Medical Image Classification
Sohaib Naim, Brian Caffo, Haris I Sair +1
Purpose: The aim of this work is to develop a neural network training framework for continual training of small amounts of medical imaging data and create heuristics to assess trai…
Deep Labeling of fMRI Brain Networks
Ammar Ahmed Pallikonda Latheef, Sejal Ghate, Zhipeng Hui +4
Resting State Networks (RSNs) of the brain extracted from Resting State functional Magnetic Resonance Imaging (RS-fMRI) are used in the pre-surgical planning to guide the neurosurg…
Active Learning in Brain Tumor Segmentation with Uncertainty Sampling, Annotation Redundancy Restriction, and Data Initialization
Daniel D Kim, Rajat S Chandra, Jian Peng +14
Deep learning models have demonstrated great potential in medical 3D imaging, but their development is limited by the expensive, large volume of annotated data required. Active lea…
Deep Labeling of fMRI Brain Networks Using Cloud Based Processing
Sejal Ghate, Alberto Santamaria-Pang, Ivan Tarapov +2
Resting state fMRI is an imaging modality which reveals brain activity localization through signal changes, in what is known as Resting State Networks (RSNs). This technique is gai…