title: Feasibility Testing: Three-dimensional Tumor Mapping in Different Orientations of Automated Breast Ultrasound.
abstract: 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.
authors.affiliation: Graduate Institute of Biomedical Informatics, College of Medical Science and Technology, Taipei Medical University, Taipei, Taiwan; Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
authors.forename: Chung-Ming
authors.initials: CM
authors.lastname: Lo
authors.affiliation: Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan; Department of Radiology, Taichung Veterans General Hospital, Taichung, Taiwan.
authors.forename: Si-Wa
authors.initials: SW
authors.lastname: Chan
authors.affiliation: Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
authors.forename: Ya-Wen
authors.initials: YW
authors.lastname: Yang
authors.affiliation: Department of Medical Imaging, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan.
authors.forename: Yeun-Chung
authors.initials: YC
authors.lastname: Chang
authors.affiliation: Department of Surgery, National Taiwan University Hospital and National Taiwan University College of Medicine, Taipei, Taiwan. Electronic address: huangcs@ntu.edu.tw.
authors.forename: Chiun-Sheng
authors.initials: CS
authors.lastname: Huang
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan.
authors.forename: Yi-Sheng
authors.initials: YS
authors.lastname: Jou
authors.affiliation: Department of Computer Science and Information Engineering, National Taiwan University, Taipei, Taiwan; Graduate Institute of Biomedical Electronics and Bioinformatics, National Taiwan University, Taipei, Taiwan. Electronic address: rfchang@csie.ntu.edu.tw.
authors.forename: Ruey-Feng
authors.initials: RF
authors.lastname: Chang
mesh_terms: D000328:Adult; D000368:Aged; D000465:Algorithms; D001943:Breast Neoplasms / Q000000981:diagnostic imaging* / Q000473:pathology*; D005240:Feasibility Studies; D005260:Female; D006801:Humans; D007089:Image Enhancement / Q000379:methods; D007090:Image Interpretation, Computer-Assisted / Q000379:methods*; D021621:Imaging, Three-Dimensional / Q000379:methods*; D000069550:Machine Learning; D008875:Middle Aged; D009367:Neoplasm Staging; D010363:Pattern Recognition, Automated / Q000379:methods*; D015203:Reproducibility of Results; D012680:Sensitivity and Specificity; D013382:Subtraction Technique; D047368:Tumor Burden; D016217:Ultrasonography, Mammary / Q000379:methods*
keywords: Automated breast ultrasound; Breast cancer; Computer-aided detection; Tumor mapping