Robust segmentation of mass-lesions in contrast-enhanced dynamic breast MR images

Lina A. Meine, Thomas Buelow, Dezheng Huo, Akiko Shimauchi, Ursula Kose, Johannes Buurman, Gillian Newstead

Research output: Contribution to journalArticlepeer-review

12 Citations (Scopus)


Purpose: To develop and evaluate a computerized segmentation method for breast MRI (BMRI) mass-lesions. Materials and Methods: A computerized segmentation algorithm was developed to segment mass-like-lesions on breast MRI. The segmentation algorithm involved: (i) interactive lesion selection, (ii) automatic intensity threshold estimation, (iii) connected component analysis, and (iv) a postprocessing procedure for hole-filling and leakage removal. Seven observers manually traced the borders of all slices of 30 mass-lesions using the same tools. To initiate the computerized segmentation, each user selected a seed-point for each lesion interactively using two methods: direct seed-point and robust region of interest (ROI) selections. The manual and computerized segmentations were compared pair-wise using the measured size and overlap to evaluate similarity, and the reproducibility of the computerized segmentation was compared with the interobserver variability of the manual delineations. Results: The observed inter- and intraobserver variations were similar (P > 0.05). Computerized segmentation using the robust ROI selection method was significantly (P < 0.001) more reproducible in measuring lesion size (stDev 1.8%) than either manual contouring (11.7%) or computerized segmentation using directly placed seed-point method (13.7%). Conclusion: The computerized segmentation method using robust ROI selection is more reproducible than manual delineation in terms of measuring the size of a mass-lesion.

Original languageEnglish
Pages (from-to)110-119
Number of pages10
JournalJournal of Magnetic Resonance Imaging
Issue number1
Publication statusPublished - 2010 Jul


  • Breast cancer
  • Computer-aided diagnosis system
  • Dynamic contrast-enhanced breast MRI
  • Mass-lesion
  • Observer study
  • Segmentation

ASJC Scopus subject areas

  • Radiology Nuclear Medicine and imaging


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