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AJNR Awards, New Junior Editors, and more. Read the latest AJNR updates

Research ArticleBrain
Open Access

Iterative Probabilistic Voxel Labeling: Automated Segmentation for Analysis of The Cancer Imaging Archive Glioblastoma Images

T.C. Steed, J.M. Treiber, K.S. Patel, Z. Taich, N.S. White, M.L. Treiber, N. Farid, B.S. Carter, A.M. Dale and C.C. Chen
American Journal of Neuroradiology April 2015, 36 (4) 678-685; DOI: https://doi.org/10.3174/ajnr.A4171
T.C. Steed
aFrom the Neurosciences Graduate Program (T.C.S.)
bSchool of Medicine (T.C.S., J.M.T.)
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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J.M. Treiber
bSchool of Medicine (T.C.S., J.M.T.)
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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K.S. Patel
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
fWeill-Cornell Medical College (K.S.P.), New York Presbyterian Hospital, New York, New York.
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Z. Taich
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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N.S. White
cMultimodal Imaging Laboratory (N.S.W., N.F., A.M.D.)
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M.L. Treiber
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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N. Farid
cMultimodal Imaging Laboratory (N.S.W., N.F., A.M.D.)
dDepartment of Radiology (N.F., A.M.D.)
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B.S. Carter
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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A.M. Dale
cMultimodal Imaging Laboratory (N.S.W., N.F., A.M.D.)
dDepartment of Radiology (N.F., A.M.D.)
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C.C. Chen
eCenter for Theoretical and Applied Neuro-Oncology, Division of Neurosurgery, Moores Cancer Center (T.C.S., J.M.T., K.S.P., Z.T., M.L.T., B.S.C., C.C.C.), University of California, San Diego, La Jolla, California
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Abstract

BACKGROUND AND PURPOSE: Robust, automated segmentation algorithms are required for quantitative analysis of large imaging datasets. We developed an automated method that identifies and labels brain tumor–associated pathology by using an iterative probabilistic voxel labeling using k-nearest neighbor and Gaussian mixture model classification. Our purpose was to develop a segmentation method which could be applied to a variety of imaging from The Cancer Imaging Archive.

MATERIALS AND METHODS: Images from 2 sets of 15 randomly selected subjects with glioblastoma from The Cancer Imaging Archive were processed by using the automated algorithm. The algorithm-defined tumor volumes were compared with those segmented by trained operators by using the Dice similarity coefficient.

RESULTS: Compared with operator volumes, algorithm-generated segmentations yielded mean Dice similarities of 0.92 ± 0.03 for contrast-enhancing volumes and 0.84 ± 0.09 for FLAIR hyperintensity volumes. These values compared favorably with the means of Dice similarity coefficients between the operator-defined segmentations: 0.92 ± 0.03 for contrast-enhancing volumes and 0.92 ± 0.05 for FLAIR hyperintensity volumes. Robust segmentations can be achieved when only postcontrast T1WI and FLAIR images are available.

CONCLUSIONS: Iterative probabilistic voxel labeling defined tumor volumes that were highly consistent with operator-defined volumes. Application of this algorithm could facilitate quantitative assessment of neuroimaging from patients with glioblastoma for both research and clinical indications.

ABBREVIATIONS:

BV
blood vessel
CEV
contrast-enhancing volume
DICE
Dice similarity coefficient
FHV
FLAIR hyperintensity volume
GMM
Gaussian mixture modeling
IPVL
iterative probabilistic voxel labeling
KNN
k-nearest neighbor
T1wCE
T1WI with contrast enhancement
TCIA
The Cancer Imaging Archive
TCGA
The Cancer Genome Atlas
  • © 2015 by American Journal of Neuroradiology

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American Journal of Neuroradiology: 36 (4)
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T.C. Steed, J.M. Treiber, K.S. Patel, Z. Taich, N.S. White, M.L. Treiber, N. Farid, B.S. Carter, A.M. Dale, C.C. Chen
Iterative Probabilistic Voxel Labeling: Automated Segmentation for Analysis of The Cancer Imaging Archive Glioblastoma Images
American Journal of Neuroradiology Apr 2015, 36 (4) 678-685; DOI: 10.3174/ajnr.A4171

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Iterative Probabilistic Voxel Labeling: Automated Segmentation for Analysis of The Cancer Imaging Archive Glioblastoma Images
T.C. Steed, J.M. Treiber, K.S. Patel, Z. Taich, N.S. White, M.L. Treiber, N. Farid, B.S. Carter, A.M. Dale, C.C. Chen
American Journal of Neuroradiology Apr 2015, 36 (4) 678-685; DOI: 10.3174/ajnr.A4171
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