Localized Sparse Code Gradient in Alzheimer's disease staging

Sidong Liu; Weidong Cai; Yang Song; Sonia Pujol; Ron Kikinis; Lingfeng Wen; David Dagan Feng

doi:10.1109/EMBC.2013.6610769

Localized Sparse Code Gradient in Alzheimer's disease staging

Sidong Liu, Weidong Cai, Yang Song, Sonia Pujol, Ron Kikinis, Lingfeng Wen, David Dagan Feng

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

19 Citations (Scopus)

Abstract

The accurate diagnosis of Alzheimer's disease (AD) at different stages is essential to identify patients at high risk of dementia and plan prevention or treatment measures accordingly. In this study, we proposed a new AD staging method for the entire spectrum of AD including the AD, Mild Cognitive Impairment with and without AD conversions, and Cognitive Normal groups. Our method embedded the high dimensional multi-view features derived from neuroimaging data into a low dimensional feature space and could form a more distinctive representation than the naive concatenated features. It also updated the testing data based on the Localized Sparse Code Gradients (LSCG) to further enhance the classification. The LSCG algorithm, validated using Magnetic Resonance Imaging data from the ADNI baseline cohort, achieved significant improvements on all diagnosis groups compared to using the original sparse coding method.

Original language	English
Title of host publication	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Publisher	Institute of Electrical and Electronics Engineers (IEEE)
Pages	5398-5401
Number of pages	4
ISBN (Print)	9781457702167
DOIs	https://doi.org/10.1109/EMBC.2013.6610769
Publication status	Published - 31 Oct 2013
Externally published	Yes
Event	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 - Osaka, Japan Duration: 3 Jul 2013 → 7 Jul 2013

Conference

Conference	2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013
Country/Territory	Japan
City	Osaka
Period	3/07/13 → 7/07/13

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10.1109/EMBC.2013.6610769

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Liu, S., Cai, W., Song, Y., Pujol, S., Kikinis, R., Wen, L., & Feng, D. D. (2013). Localized Sparse Code Gradient in Alzheimer's disease staging. In 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 (pp. 5398-5401). Article 6610769 Institute of Electrical and Electronics Engineers (IEEE). https://doi.org/10.1109/EMBC.2013.6610769

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title = "Localized Sparse Code Gradient in Alzheimer's disease staging",

abstract = "The accurate diagnosis of Alzheimer's disease (AD) at different stages is essential to identify patients at high risk of dementia and plan prevention or treatment measures accordingly. In this study, we proposed a new AD staging method for the entire spectrum of AD including the AD, Mild Cognitive Impairment with and without AD conversions, and Cognitive Normal groups. Our method embedded the high dimensional multi-view features derived from neuroimaging data into a low dimensional feature space and could form a more distinctive representation than the naive concatenated features. It also updated the testing data based on the Localized Sparse Code Gradients (LSCG) to further enhance the classification. The LSCG algorithm, validated using Magnetic Resonance Imaging data from the ADNI baseline cohort, achieved significant improvements on all diagnosis groups compared to using the original sparse coding method.",

author = "Sidong Liu and Weidong Cai and Yang Song and Sonia Pujol and Ron Kikinis and Lingfeng Wen and Feng, {David Dagan}",

year = "2013",

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doi = "10.1109/EMBC.2013.6610769",

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booktitle = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013",

publisher = "Institute of Electrical and Electronics Engineers (IEEE)",

address = "United States",

note = "2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013 ; Conference date: 03-07-2013 Through 07-07-2013",

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Liu, S, Cai, W, Song, Y, Pujol, S, Kikinis, R, Wen, L & Feng, DD 2013, Localized Sparse Code Gradient in Alzheimer's disease staging. in 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013., 6610769, Institute of Electrical and Electronics Engineers (IEEE), pp. 5398-5401, 2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013, Osaka, Japan, 3/07/13. https://doi.org/10.1109/EMBC.2013.6610769

Localized Sparse Code Gradient in Alzheimer's disease staging. / Liu, Sidong; Cai, Weidong; Song, Yang et al.
2013 35th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2013. Institute of Electrical and Electronics Engineers (IEEE), 2013. p. 5398-5401 6610769.

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

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AU - Wen, Lingfeng

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AB - The accurate diagnosis of Alzheimer's disease (AD) at different stages is essential to identify patients at high risk of dementia and plan prevention or treatment measures accordingly. In this study, we proposed a new AD staging method for the entire spectrum of AD including the AD, Mild Cognitive Impairment with and without AD conversions, and Cognitive Normal groups. Our method embedded the high dimensional multi-view features derived from neuroimaging data into a low dimensional feature space and could form a more distinctive representation than the naive concatenated features. It also updated the testing data based on the Localized Sparse Code Gradients (LSCG) to further enhance the classification. The LSCG algorithm, validated using Magnetic Resonance Imaging data from the ADNI baseline cohort, achieved significant improvements on all diagnosis groups compared to using the original sparse coding method.

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Localized Sparse Code Gradient in Alzheimer's disease staging

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