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

doi:10.1109/BigComp.2018.00103

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 proceeding › Conference 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 language	English
Title of host publication	Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
Publisher	Institute of Electrical and Electronics Engineers Inc.
Pages	595-598
Number of pages	4
ISBN (Electronic)	9781538636497
DOIs	https://doi.org/10.1109/BigComp.2018.00103
Publication status	Published - 2018 May 25
Event	2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018 - Shanghai, China Duration: 2018 Jan 15 → 2018 Jan 18

Publication series

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

Other

Other	2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018
Country/Territory	China
City	Shanghai
Period	18/1/15 → 18/1/18

Bibliographical note

Publisher Copyright:
© 2018 IEEE.

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

Access to Document

10.1109/BigComp.2018.00103

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). Article 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

Longitudinal Sparse Regression for Neuroimage Based Consciousness Assessing and Tracking of Hydrocephalus Patients. / Chen, Sen; Tang, Weijun; Hu, Jin et al.
Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018. Institute of Electrical and Electronics Engineers Inc., 2018. p. 595-598 8367183 (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018).

Research output: Chapter in Book/Report/Conference proceeding › Conference contribution

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., 8367183, Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018, Institute of Electrical and Electronics Engineers Inc., pp. 595-598, 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018, Shanghai, China, 18/1/15. https://doi.org/10.1109/BigComp.2018.00103

Chen S, Tang W, Hu J, Cheng Y, Wang Q, Wu X et al. 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. Institute of Electrical and Electronics Engineers Inc. 2018. p. 595-598. 8367183. (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018). doi: 10.1109/BigComp.2018.00103

Chen, Sen ; Tang, Weijun ; Hu, Jin et al. / Longitudinal Sparse Regression for Neuroimage Based Consciousness Assessing and Tracking of Hydrocephalus Patients. Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018. Institute of Electrical and Electronics Engineers Inc., 2018. pp. 595-598 (Proceedings - 2018 IEEE International Conference on Big Data and Smart Computing, BigComp 2018).

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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.",

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author = "Sen Chen and Weijun Tang and Jin Hu and Yawang Cheng and Qian Wang and Xuehai Wu and Dinggang Shen",

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

Abstract

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Keywords

ASJC Scopus subject areas

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