Abstract
Breast tumour is a leading cause for woman mortality. While cancer screening is mostly performed by the use of mammography, 3D ultrasound seems better suited for the purpose. It gives 3D view of the breast structure, is less painful and can be considered less invasive, as the patient is not exposed to x-ray radiation. Therefore, the development of automatic algorithms that remove from the diagnostician the tedious and time consuming task of finding suspicious regions in large volumetric images is of key importance. The paper concludes a preliminary study for the development of an automatic method for breast tumour segmentation in ultrasound volumetric images. The method is based on multiscale blob detector, watershed transform with the final precise segmentation performed by an active contour approach. The method has been evaluated using 16 volumes acquired from a breast phantom containing nodules. The obtained results reached up to 94.68% sensitivity, 100.00% specificity, 92.63% Dice index, 99.95% Accuracy, 92.61% Cohen’s Kappa index and 86.28% Jaccard index.
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Acknowledgement
This research was supported by the Polish National Centre for Research and Development (NCBR), grant no. STRATEGMED2/267398/ 3/NCBR/2015. The authors would also like to thank Andre Woloshuk for his English language corrections.
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Wieclawek, W., Rudzki, M., Wijata, A., Galinska, M. (2019). Preliminary Development of an Automatic Breast Tumour Segmentation Algorithm from Ultrasound Volumetric Images. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_7
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