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Proceedings Paper

Histogram-based classification with Gaussian mixture modeling for GBM tumor treatment response using ADC map
Author(s): Jing Huo; Hyun J. Kim; Whitney B. Pope; Kazunori Okada; Jeffery R. Alger; Yang Wang; Jonathan G. Goldin; Matthew S. Brown
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Paper Abstract

This study applied a Gaussian Mixture Model (GMM) to apparent diffusion coefficient (ADC) histograms to evaluate glioblastoma multiforme (GBM) tumor treatment response using diffusion weighted (DW) MR images. ADC mapping, calculated from DW images, has been shown to reveal changes in the tumor's microenvironment preceding morphologic tumor changes. In this study, we investigated the effectiveness of features that represent changes from pre- and post-treatment tumor ADC histograms to detect treatment response. The main contribution of this work is to model the ADC histogram as the composition of two components, fitted by GMM with expectation maximization (EM) algorithm. For both pre- and post-treatment scans taken 5-7 weeks apart, we obtained the tumor ADC histogram, calculated the two-component features, as well as the other standard histogram-based features, and applied supervised learning for classification. We evaluated our approach with data from 85 patients with GBM under chemotherapy, in which 33 responded and 52 did not respond based on tumor size reduction. We compared AdaBoost and random forests classification algorithms, using ten-fold cross validation, resulting in a best accuracy of 69.41%.

Paper Details

Date Published: 3 March 2009
PDF: 7 pages
Proc. SPIE 7260, Medical Imaging 2009: Computer-Aided Diagnosis, 72601Y (3 March 2009); doi: 10.1117/12.812923
Show Author Affiliations
Jing Huo, Univ. of California, Los Angeles (United States)
Hyun J. Kim, Univ. of California, Los Angeles (United States)
Whitney B. Pope, Univ. of California, Los Angeles (United States)
Kazunori Okada, San Francisco State Univ. (United States)
Jeffery R. Alger, Univ. of California, Los Angeles (United States)
Yang Wang, Univ. of California, Los Angeles (United States)
Jonathan G. Goldin, Univ. of California, Los Angeles (United States)
Matthew S. Brown, Univ. of California, Los Angeles (United States)

Published in SPIE Proceedings Vol. 7260:
Medical Imaging 2009: Computer-Aided Diagnosis
Nico Karssemeijer; Maryellen L. Giger, Editor(s)

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