Longitudinal Sparse Regression for Neuroimage Based Consciousness Assessing and Tracking of Hydrocephalus Patients

Sen Chen, Weijun Tang, Jin Hu, Yawang Cheng, Qian Wang, Xuehai Wu, Dinggang Shen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract

Hydrocephalus is a condition that causes ventricle enlargement by pathological accumulation of cerebrospinal fluid (CSF) and ends with different levels of disorders of consciousness (DOCs). Assessment of the consciousness level will help for the planning of the treatment of the patients. In this paper, a longitudinal sparse regression model featured by the temporal constraint is proposed to assess the levels of consciousness for hydrocephalus patients and to track their temporal alterations based on magnetic resonance (MR) images. Specifically, for the time points before and after neurosurgeries, we extract features from the corresponding MR scans and then regress out the clinical scores that reflect the respective consciousness levels. The longitudinal regression model can thus be applied to automatically track and evaluate the consciousness level change for individual patients, while the reading of the regression can act as an important indicator for the planning of subsequent treatment in clinical practice.

Original languageEnglish
Title of host publicationProceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages595-598
Number of pages4
ISBN (Electronic)9781538636497
DOIs
Publication statusPublished - 2018 May 25
Externally publishedYes
Event2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 - Shanghai, China
Duration: 2018 Jan 152018 Jan 18

Publication series

NameProceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018

Other

Other2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
CountryChina
CityShanghai
Period18/1/1518/1/18

Keywords

  • disorder of consciousness
  • feature selection
  • hydrocephalus
  • longitudinal sparse regression

ASJC Scopus subject areas

  • Artificial Intelligence
  • Computer Networks and Communications
  • Information Systems
  • Information Systems and Management

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  • Cite this

    Chen, S., Tang, W., Hu, J., Cheng, Y., Wang, Q., Wu, X., & Shen, D. (2018). Longitudinal Sparse Regression for Neuroimage Based Consciousness Assessing and Tracking of Hydrocephalus Patients. In Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 (pp. 595-598). [8367183] (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018). Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/BigComp.2018.00103