Feasibility Testing: Three-dimensional Tumor Mapping in Different Orientations of Automated Breast Ultrasound

Chung Ming Lo, Si Wa Chan, Ya Wen Yang, Yeun Chung Chang, Chiun Sheng Huang, Yi Sheng Jou, Ruey Feng Chang

Research output: Contribution to journalArticlepeer-review

6 Citations (Scopus)


A tumor-mapping algorithm was proposed to identify the same regions in different passes of automated breast ultrasound (ABUS). A total of 53 abnormal passes with 41 biopsy-proven tumors and 13 normal passes were collected. After computer-aided tumor detection, a mapping pair was composed of a detected region in one pass and another region in another pass. Location criteria, including the radial position as on a clock, the relative distance and the distance to the nipple, were used to extract mapping pairs with close regions. Quantitative intensity, morphology, texture and location features were then combined in a classifier for further classification. The performance of the classifier achieved a mapping rate of 80.39% (41/51), with an error rate of 5.97% (4/67). The trade-offs between the mapping and error rates were evaluated, and Az = 0.9094 was obtained. The proposed tumor-mapping algorithm was capable of automatically providing location correspondence information that would be helpful in reviews of ABUS examinations.

Original languageEnglish
Pages (from-to)1201-1210
Number of pages10
JournalUltrasound in Medicine and Biology
Issue number5
Publication statusPublished - May 1 2016


  • Automated breast ultrasound
  • Breast cancer
  • Computer-aided detection
  • Tumor mapping

ASJC Scopus subject areas

  • Radiological and Ultrasound Technology
  • Biophysics
  • Acoustics and Ultrasonics


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