Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

T. Hopp; M. Zapf; N. V. Ruiter

doi:10.1117/12.2044376

20 March 2014 Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting

T. Hopp, M. Zapf, N. V. Ruiter

Author Affiliations +

Proceedings Volume 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography; 90401R (2014) https://doi.org/10.1117/12.2044376
Event: SPIE Medical Imaging, 2014, San Diego, California, United States

Abstract

An essential processing step for comparison of Ultrasound Computer Tomography images to other modalities, as well as for the use in further image processing, is to segment the breast from the background. In this work we present a (semi-) automated 3D segmentation method which is based on the detection of the breast boundary in coronal slice images and a subsequent surface fitting. The method was evaluated using a software phantom and in-vivo data. The fully automatically processed phantom results showed that a segmentation of approx. 10% of the slices of a dataset is sufficient to recover the overall breast shape. Application to 16 in-vivo datasets was performed successfully using semi-automated processing, i.e. using a graphical user interface for manual corrections of the automated breast boundary detection. The processing time for the segmentation of an in-vivo dataset could be significantly reduced by a factor of four compared to a fully manual segmentation. Comparison to manually segmented images identified a smoother surface for the semi-automated segmentation with an average of 11% of differing voxels and an average surface deviation of 2mm. Limitations of the edge detection may be overcome by future updates of the KIT USCT system, allowing a fully-automated usage of our segmentation approach.

Citation Download Citation

T. Hopp, M. Zapf, and N. V. Ruiter "Segmentation of 3D ultrasound computer tomography reflection images using edge detection and surface fitting", Proc. SPIE 9040, Medical Imaging 2014: Ultrasonic Imaging and Tomography, 90401R (20 March 2014); https://doi.org/10.1117/12.2044376

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