Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury

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Home < Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury

Editing Semiautomatic longitudinal segmentation of MR volumes in traumatic brain injury

Key Investigators

  • UCLA: Andrei Irimia, Micah Chambers
  • Kitware: Danielle Pace, Stephen Aylward

Objective

We are developing methods for analyzing MR volumes of traumatic brain injury. The goal is to provide a tool for the automatic segmentation of TBI from multimodal neuroimaging volume data.

Approach

The UCLA and UNC/Kitware teams will be interacting and providing feedback with regard to an upcoming Slicer implementation of an automatic segmentation algorithm for TBI.

Progress

Delivery Mechanism

This work will be delivered to the NA-MIC Kit as a (please select the appropriate options by noting YES against them below)

  1. Slicer Module
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