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Multi-scale Blood Vessel Detection and Segmentation in Breast MRIs

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Abstract

An algorithm is proposed to perform segmentation of blood vessels in 3D breast MRIs. The blood vessels play an essential role as an additional tool to detect tumors. Large concentration of blood vessels can indicate a malignant mass. Radiologists use a maximum-intensity projection to expose the vasculature. However, the breast is a challenging organ in identifying vascular structures, because of noise and fat tissues. There are several existing algorithms to detect blood vessels in MRI, but those usually prove insufficient when it comes to the breast. Our algorithm provides a three-dimensional model of blood vessels by utilizing texture enhancement, Hessian-based methods and blood vessel completion by center line tracking. We compared the algorithm results to manually segmented images done by radiologists in 24 different patients. They yielded in 86% sensitivity to the ground truth and 88.3% specificity. It also appears that by employing mass detection as the last step, our algorithm can provide a helpful tool for tumor enhancement and automated detection of breast cancer.

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Acknowledgements

This work was supported in part by the Israel Office of the Chief Scientist under Grant BS123456.

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Author notes

  1. Gilad Kahala and Miri Sklair have contributed equally to this work.

Authors and Affiliations

  1. Electrical Engineering Department, Tel Aviv University, Haim Levanon st. 8, Tel Aviv, 6997801, Israel

    Gilad Kahala & Hedva Spitzer

  2. Sheba Medical Center, Ramat Gan, 5262100, Israel

    Miri Sklair

Authors
  1. Gilad Kahala
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  2. Miri Sklair
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  3. Hedva Spitzer
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Correspondence to Gilad Kahala.

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Kahala, G., Sklair, M. & Spitzer, H. Multi-scale Blood Vessel Detection and Segmentation in Breast MRIs. J. Med. Biol. Eng. 39, 424–430 (2019). https://doi.org/10.1007/s40846-018-0418-6

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  • DOI: https://doi.org/10.1007/s40846-018-0418-6

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