Document Detail


Multispectral co-occurrence with three random variables in dynamic contrast enhanced magnetic resonance imaging of breast cancer.
MedLine Citation:
PMID:  18815094     Owner:  NLM     Status:  MEDLINE    
Abstract/OtherAbstract:
Presented is a new computer-aided multispectral image processing method which is used in three spatial dimensions and one spectral dimension where the dynamic, contrast enhanced magnetic resonance parameter maps derived from voxel-wise model-fitting represent the spectral dimension. The method is based on co-occurrence analysis using a 3-D window of observation which introduces an automated identification of suspicious lesions. The co-occurrence analysis defines 21 different statistical features, a subset of which were input to a neural network classifier where the assessments of the voxel-wise majority of a group of radiologist readings were used as the gold standard. The voxel-wise true positive fraction (TPF) and false positive fraction (FPF) results of the computer classifier were statistically indistinguishable from the TPF and FPF results of the readers using a one sample paired t-test. In order to observe the generality of the method, two different groups of studies were used with widely different image acquisition specifications.
Authors:
Mehmet C Kale; Bradley D Clymer; Regina M Koch; Johannes T Heverhagen; Steffen Sammet; Robert Stevens; Michael V Knopp
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Publication Detail:
Type:  Journal Article; Research Support, N.I.H., Extramural; Research Support, Non-U.S. Gov't    
Journal Detail:
Title:  IEEE transactions on medical imaging     Volume:  27     ISSN:  1558-254X     ISO Abbreviation:  IEEE Trans Med Imaging     Publication Date:  2008 Oct 
Date Detail:
Created Date:  2008-09-25     Completed Date:  2008-10-24     Revised Date:  2012-04-24    
Medline Journal Info:
Nlm Unique ID:  8310780     Medline TA:  IEEE Trans Med Imaging     Country:  United States    
Other Details:
Languages:  eng     Pagination:  1425-31     Citation Subset:  IM    
Affiliation:
Department of Electrical and Computer Engineering, The Ohio State University, Columbus, OH 43210, USA.
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MeSH Terms
Descriptor/Qualifier:
Algorithms*
Artificial Intelligence*
Breast Neoplasms / diagnosis*
Contrast Media*
Female
Humans
Image Enhancement / methods
Image Interpretation, Computer-Assisted / methods*
Imaging, Three-Dimensional / methods*
Magnetic Resonance Imaging / methods*
Pattern Recognition, Automated / methods*
Reproducibility of Results
Sensitivity and Specificity
Grant Support
ID/Acronym/Agency:
P20EB000591/EB/NIBIB NIH HHS
Chemical
Reg. No./Substance:
0/Contrast Media

From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine


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