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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Belkacem-Boussaid, K. Pennell, M. Lozanski, G. Shana'ah, A. Gurcan, M.N. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Pathology, The Ohio State University; E312 Doan Hall, 410 W 10th Ave., Columbus, 43210, USA (Lozanski, G.; Shana'ah, A.) || Division of Biostatistics, College of Public Health, Ohio State University; B-115 Starling-Loving Hall 320 W, 10th Ave.; Columbus, 43210, USA (Pennell, M.) || Department of Biomedical Informatics, Ohio State University; 333 W. 10th Ave., Columbus, 43210, USA (Belkacem-Boussaid, K.; Gurcan, M.N.) |
| Abstract | In this paper, a novel automated method to recognize centroblast (CB) cells from non-centroblast (non-CB) cells in follicular lymphoma cases is developed and its performance is evaluated against consensus of 30 board-certified hematopathologists. Morphometric and color texture features are used in the training and testing of a supervised quadratic discriminate analysis (QDA) classifier. The novelty of our method resides in the identification of the CB cells with prior information, and the introduction of the principal component analysis (PCA) in the spectral domain to extract texture color features. A graphical user interface was developed to display CB and non-CB cells without the computer-classification to the hematopathologists and their responses were recorded by the software. Our automated grading system performed well when compared to consensus diagnosis of 30 hematopathologists. Automated classification can identify centroblast cells (CB) from non-centroblast cells (non-CB) with a sensitivity and specificity of 81.8%, 86.4%, respectively. The developed system was tested on an independent set of cases with a consensus of 16 or 20 hematopathologists. The sensitivity and specificity of the developed system is higher when the ground truth is based on the consensus of 20 pathologists. |
| Starting Page | 1411 |
| Ending Page | 1414 |
| File Size | 655448 |
| Page Count | 4 |
| File Format | |
| ISBN | 9781424441259 |
| ISSN | 19457928 |
| DOI | 10.1109/ISBI.2010.5490263 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-14 |
| Publisher Place | Netherlands |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Image color analysis Pathology Biomedical imaging Medical diagnostic imaging Principal component analysis Sensitivity and specificity Coronary arteriosclerosis Diseases Application software Data mining statistical analysis Follicular lymphoma CB cell non-CB cell morphological features color texture features principal components analysis spectral domain classification |
| Content Type | Text |
| Resource Type | Article |
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