Identification, Segmentation, and Image Property Study of Acute Infarcts in Diffusion-Weighted Images by Using a Probabilistic Neural Network and Adaptive Gaussian Mixture Model

Academic Radiology

Volumn 13, Issue 12, 2006, Pages 1474-1484

  Bhanu Prakash, KN ^a   Gupta, Varsha ^a   Bilello, Michel ^b   Beauchamp, Norman J ^c   Nowinski, Wieslaw L ^a  

^a AGENCY FOR SCIENCE   (Singapore)

^b UNIVERSITY OF PENNSYLVANIA   (United States)

^c UNIVERSITY OF WASHINGTON MEDICAL CENTER   (United States)

Author keywords

Artifact; Diffusion; Gaussian mixture model; Infarct; Segmentation; Stroke

Indexed keywords

ALGORITHM; ARTICLE; ARTIFACT REDUCTION; BAYES THEOREM; BRAIN INFARCTION; BRAIN INFARCTION SIZE; BRAIN SIZE; BRAIN SLICE; COMPUTER ANALYSIS; DIAGNOSTIC ACCURACY; DIAGNOSTIC VALUE; DIFFUSION WEIGHTED IMAGING; DISPLAY SYSTEM; FALSE NEGATIVE RESULT; FALSE POSITIVE RESULT; IMAGE DISPLAY; IMAGE QUALITY; NERVE CELL NETWORK; NORMAL DISTRIBUTION; PRIORITY JOURNAL; PROBABILITY; RECEIVER OPERATING CHARACTERISTIC; SAMPLE SIZE; STROKE PATIENT;

ALGORITHMS; ARTIFACTS; CEREBRAL INFARCTION; FALSE NEGATIVE REACTIONS; FALSE POSITIVE REACTIONS; HUMANS; IMAGE PROCESSING, COMPUTER-ASSISTED; NEURAL NETWORKS (COMPUTER); NORMAL DISTRIBUTION; ROC CURVE; TOMOGRAPHY, X-RAY COMPUTED;

EID: 33751402210     PISSN: 10766332     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.acra.2006.09.045     Document Type: Article

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