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DL_ZNet_3D_BrainSeg

3D ZNet Brain Segmentation DNN Model for MRI Brain Tumor Segmentation

Table of contents

Overview

Neuroimaging segmentation is a challenging task because of the complex structure, organization, anatomy, function and physiology of the brain. This project introduces Znet, an AI encoder-decoder deep learning technique for segmenting 3D MR images.

Code

The complete self-cntained python code is available in the SOCR_3D_ZNET_python_code_V1 folder.

Team

SOCR Team, Mohammad Ashraf Ottom, Hanif Abdul Rahman, Iyad M. Alazzam, and Ivo D. Dinov, and others.

Acknowledgments

This work is supported in part by NIH grants P20 NR015331, UL1TR002240, P30 DK089503, UL1TR002240, and NSF grants 1916425, 1734853, 1636840, 1416953, 0716055 and 1023115. Students, trainees, scholars, and researchers from SOCR, BDDS, MNORC, MIDAS, MADC, MICHR, and the broad R-statistical computing community have contributed ideas, code, and support.

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3D ZNet Brain Segmentation DNN Model

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