Stepwise logistic regression analysis of tumor contour features for breast ultrasound diagnosis

Huihua Kenny Chiang*, Chui Mei Tiu, Guo Shian Hung, Shiao Chi Wu, Tiffany Y. Chang, Yi Hong Chou

*Corresponding author for this work

Research output: Contribution to journalConference articlepeer-review

9 Scopus citations

Abstract

To assist the ultrasound (US) diagnosis of solid breast tumors by using stepwise logistic regression (SLR) analysis of tumor contour features, we reviewed 111 digitized US images of breast tumors. They were 40 benign breast tumors (fibroadenomas), and 71 infiltrative ductal carcinomas. The contour features were calculated by the radial length. A SLR model with contour features was used to classify tumors as benign or malignant. The accuracy of our model with contour features for classifying malignancies was 91.0% (101 of 111 tumors), the sensitivity was 97.2% (69 of 71), the specificity was 80.0% (32 of 40).

Original languageEnglish
Pages (from-to)1303-1306
Number of pages4
JournalProceedings of the IEEE Ultrasonics Symposium
Volume2
DOIs
StatePublished - Oct 2001
Event2001 Ultrasonics Symposium - Atlanta, GA, United States
Duration: 6 Oct 200110 Oct 2001

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