| Computer-aided US diagnosis of breast lesions by using cell-based contour grouping. | |
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MedLine Citation:
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PMID: 20501714 Owner: NLM Status: MEDLINE |
Abstract/OtherAbstract:
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PURPOSE: To develop a computer-aided diagnostic algorithm with automatic boundary delineation for differential diagnosis of benign and malignant breast lesions at ultrasonography (US) and investigate the effect of boundary quality on the performance of a computer-aided diagnostic algorithm. MATERIALS AND METHODS: This was an institutional review board-approved retrospective study with waiver of informed consent. A cell-based contour grouping (CBCG) segmentation algorithm was used to delineate the lesion boundaries automatically. Seven morphologic features were extracted. The classifier was a logistic regression function. Five hundred twenty breast US scans were obtained from 520 subjects (age range, 15-89 years), including 275 benign (mean size, 15 mm; range, 5-35 mm) and 245 malignant (mean size, 18 mm; range, 8-29 mm) lesions. The newly developed computer-aided diagnostic algorithm was evaluated on the basis of boundary quality and differentiation performance. The segmentation algorithms and features in two conventional computer-aided diagnostic algorithms were used for comparative study. RESULTS: The CBCG-generated boundaries were shown to be comparable with the manually delineated boundaries. The area under the receiver operating characteristic curve (AUC) and differentiation accuracy were 0.968 +/- 0.010 and 93.1% +/- 0.7, respectively, for all 520 breast lesions. At the 5% significance level, the newly developed algorithm was shown to be superior to the use of the boundaries and features of the two conventional computer-aided diagnostic algorithms in terms of AUC (0.974 +/- 0.007 versus 0.890 +/- 0.008 and 0.788 +/- 0.024, respectively). CONCLUSION: The newly developed computer-aided diagnostic algorithm that used a CBCG segmentation method to measure boundaries achieved a high differentiation performance. |
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Authors:
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Jie-Zhi Cheng; Yi-Hong Chou; Chiun-Sheng Huang; Yeun-Chung Chang; Chui-Mei Tiu; Kuei-Wu Chen; Chung-Ming Chen |
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Publication Detail:
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Type: Comparative Study; Journal Article; Research Support, Non-U.S. Gov't |
Journal Detail:
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Title: Radiology Volume: 255 ISSN: 1527-1315 ISO Abbreviation: Radiology Publication Date: 2010 Jun |
Date Detail:
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Created Date: 2010-05-26 Completed Date: 2010-07-15 Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 0401260 Medline TA: Radiology Country: United States |
Other Details:
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Languages: eng Pagination: 746-54 Citation Subset: AIM; IM |
Copyright Information:
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Copyright RSNA, 2010 |
Affiliation:
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Institute of Biomedical Engineering, College of Medicine, and College of Engineering, National Taiwan University, #1, Sec. 1, Jen-Ai Road, Taipei 100, Taiwan. |
Export Citation:
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APA/MLA Format Download EndNote Download BibTex |
| MeSH Terms | |
Descriptor/Qualifier:
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Adolescent Adult Aged Aged, 80 and over Algorithms* Breast Diseases / pathology, ultrasonography* Diagnosis, Computer-Assisted / methods* Diagnosis, Differential Female Humans Logistic Models Middle Aged ROC Curve Retrospective Studies Ultrasonography, Mammary* |
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