A fully automatic lesion detection method for DCE-MRI fat-suppressed breast images

Anna Vignati, Valentina Giannini, Alberto Bert, Massimo Deluca, Lia Morra, Diego Persano, Laura Martincich, Daniele Regge

Research output: Chapter in Book/Report/Conference proceedingConference contribution


Dynamic Contrast Enhanced MRI (DCE-MRI) has today a well-established role, complementary to routine imaging techniques for breast cancer diagnosis such as mammography. Despite its undoubted clinical advantages, DCE-MRI data analysis is time-consuming and Computer Aided Diagnosis (CAD) systems are required to help radiologists. Segmentation is one of the key step of every CAD image processing pipeline, but most techniques available require human interaction. We here present the preliminary results of a fully automatic lesion detection method, capable of dealing with fat suppression image acquisition sequences, which represents a challenge for image processing algorithms due to the low SNR. The method is based on four fundamental steps: registration to correct for motion artifacts; anatomical segmentation to discard anatomical structures located outside clinically interesting lesions; lesion detection to select enhanced areas and false positive reduction based on morphological and kinetic criteria. The testing set was composed by 13 cases and included 27 lesions (10 benign and 17 malignant) of diameter > 5 mm. The system achieves a per-lesion sensitivity of 93%, while yielding an acceptable number of false positives (26 on average). The results of our segmentation algorithm were verified by visual inspection, and qualitative comparison with a manual segmentation yielded encouraging results.

Original languageEnglish
Title of host publicationProgress in Biomedical Optics and Imaging - Proceedings of SPIE
Publication statusPublished - 2009
EventMedical Imaging 2009: Computer-Aided Diagnosis - Lake Buena Vista, FL, United States
Duration: Feb 10 2009Feb 12 2009


OtherMedical Imaging 2009: Computer-Aided Diagnosis
Country/TerritoryUnited States
CityLake Buena Vista, FL


  • Automatic segmentation
  • Breast cancer
  • CAD
  • Fat suppression

ASJC Scopus subject areas

  • Atomic and Molecular Physics, and Optics
  • Electronic, Optical and Magnetic Materials
  • Biomaterials
  • Radiology Nuclear Medicine and imaging


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