Finding lesion correspondences in different views of automated 3D breast ultrasound

Tao Tan, Bram Platel, Michael Hicks, Ritse M. Mann, Nico Karssemeijer

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

2 Citations (Scopus)


Screening with automated 3D breast ultrasound (ABUS) is gaining popularity. However, the acquisition of multiple views required to cover an entire breast makes radiologic reading time-consuming. Linking lesions across views can facilitate the reading process. In this paper, we propose a method to automatically predict the position of a lesion in the target ABUS views, given the location of the lesion in a source ABUS view. We combine features describing the lesion location with respect to the nipple, the transducer and the chestwall, with features describing lesion properties such as intensity, spiculation, blobness, contrast and lesion likelihood. By using a grid search strategy, the location of the lesion was predicted in the target view. Our method achieved an error of 15.64 mm±16.13 mm. The error is small enough to help locate the lesion with minor additional interaction.

Original languageEnglish
Title of host publicationMedical Imaging 2013
Subtitle of host publicationComputer-Aided Diagnosis
Publication statusPublished - 2013
Externally publishedYes
EventMedical Imaging 2013: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: 12 Feb 201314 Feb 2013

Publication series

NameProceedings of SPIE - The International Society for Optical Engineering
ISSN (Print)0277-786X


ConferenceMedical Imaging 2013: Computer-Aided Diagnosis
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Automated 3D breast ultrasound
  • Automated linkage
  • Breast cancer
  • CAD


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