Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects

Advances in data preprocessing for biomedical data fusion: An overview of the methods, challenges, and prospects

Due to the proliferation of biomedical imaging modalities, such as Photo-acoustic Tomography, Computed Tomography (CT), Optical Microscopy and Tomography, etc., massive amounts of data are generated on a daily basis. While massive biomedical data sets yield more information about pathologies, they a...

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Bibliographic Details
Main Authors: Shuihua Wang, M Emre Celebi, Yu-Dong Zhang, Xiang Yu, Siyuan Lu, Xujing Yao, Qinghua Zhou, Miguel Martinez-Garcia, Yingli Tian, Juan M Gorriz, Ivan Tyukin
Format: Default Article
Published: 2021
Subjects:
Artificial intelligence not elsewhere classified
Data fusion
Noise
Data scarcity
High dimensionality
Missing data
Small dataset
Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Computer Science
MEDICAL IMAGE REGISTRATION
PARTIAL LEAST-SQUARES
HANDLING MISSING DATA
CONVOLUTIONAL NEURAL-NETWORK
PRINCIPAL COMPONENT ANALYSIS
ACTIVE CONTOUR MODELS
MR-TRUS FUSION
MULTIPLE IMPUTATION
ALZHEIMERS-DISEASE
ANISOTROPIC DIFFUSION
Artificial Intelligence & Image Processing
Artificial Intelligence and Image Processing
Online Access:https://hdl.handle.net/2134/16577729.v1
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https://hdl.handle.net/2134/16577729.v1

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