Quantitative analysis of brain herniation from non-contrast CT images using deep learning-Reference-Cited by-同舟云学术

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Quantitative analysis of brain herniation from non-contrast CT images using deep learning

Published:2021-02 Issue: Volume:349 Page:109033
ISSN:0165-0270
Container-title:Journal of Neuroscience Methods
language:en
Short-container-title:Journal of Neuroscience Methods

Author:

Nag Manas Kumar,Gupta Akshat,Hariharasudhan A.S.,Sadhu Anup Kumar,Das Abir,Ghosh Nirmalya

Funder

Council for Scientific and Industrial Research (CSIR), New Delhi, India

Publisher

Elsevier BV

Subject

General Neuroscience

Reference24 articles.

1. Segnet: a deep convolutional encoder-decoder architecture for image All these predictors were co segmentation;Badrinarayanan;IEEE Trans. Pattern Anal. Mach. Intell.,2017

2. Actual midline estimation from brain CT scan using multiple regions shape matching;Chen,2010

3. Automatic estimation of midline shift in patients with cerebral glioma based on enhanced voigt model and local symmetry;Chen;Australas. Phys. Eng. Sci. Med.,2015

4. Analyzing risk factors for late posttraumatic seizures: a prospective, multicenter investigation;Englander;Arch. Phys. Med. Rehabil.,2003

5. Guest editorial deep learning in medical imaging: overview and future promise of an exciting new technique;Greenspan;IEEE Trans. Med. Imaging,2016

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