Deep Learning-Based Tract Classification of Preoperative DWI Tractography Advances the Prediction of Short-Term Postoperative Language Improvement in Children With Drug-Resistant Epilepsy.

Journal: IEEE transactions on bio-medical engineering
PMID:

Abstract

OBJECTIVE: To develop an innovative deep convolutional neural network (DCNN)-based tract classification to enhance the prediction of short-term postoperative language improvement using axonal connectivity markers derived from specific language modular networks (LMNs) within the preoperative whole-brain diffusion-weighted imaging connectome (wDWIC).

Authors

  • Min-Hee Lee
  • Soumyanil Banerjee
    Computer Science, Wayne State University, Detroit, Michigan, USA.
  • Hiroshi Uda
  • Alanna Carlson
  • Ming Dong
    Department of Computer Science, Wayne State University.
  • Robert Rothermel
  • Csaba Juhasz
  • Eishi Asano
  • Jeong-Won Jeong