Inadequate dataset learning for major depressive disorder MRI semantic classification-Reference-Cited by-同舟云学术

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Inadequate dataset learning for major depressive disorder MRI semantic classification

Published:2022-02-15 Issue:6 Volume:16 Page:1648-1656
ISSN:1751-9659
Container-title:IET Image Processing
language:en
Short-container-title:IET Image Processing

Author:

Liu Jie¹,Dey Nilanjan²,Crespo Ruben González³,Shi Fuqian⁴,Liu Chanjuan¹^ORCID

Affiliation:

1. Department of Information Wenzhou Medical University Wenzhou Peoples' Republic of China

2. Department of Computer Science and Engineering JIS University Kolkata India

3. Department of Computer Science and Technology Universidad Internacional de La Rioja Logroño Spain

4. Rutgers Cancer Institute of New Jersey Rutgers University‐New Brunswick New Jersey USA

Publisher

Institution of Engineering and Technology (IET)

Subject

Electrical and Electronic Engineering,Computer Vision and Pattern Recognition,Signal Processing,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1049/ipr2.12437

Reference34 articles.

1. PET and SPECT Imaging of the Brain: History, Technical Considerations, Applications, and Radiotracers

2. Functional imaging of memory processes in humans: Positron emission tomography and functional magnetic resonance imaging

3. Evaluating the diagnostic utility of applying a machine learning algorithm to diffusion tensor MRI measures in individuals with major depressive disorder

4. Reproducibility of functional brain alterations in major depressive disorder: Evidence from a multisite resting-state functional MRI study with 1,434 individuals

5. Deep learning and transfer learning features for plankton classification

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