Tissue classification and contrast agent separation in spectral micro CT using Medipix3 CdTe detector

Juan C. R. Luna; Ian Harmon; Mini Das

doi:10.1117/12.2613361

11 April 2022 Tissue classification and contrast agent separation in spectral micro CT using Medipix3 CdTe detector

Juan C. R. Luna, Ian Harmon, Mini Das

Author Affiliations +

Proceedings Volume PC12031, Medical Imaging 2022: Physics of Medical Imaging; PC120310N (2022) https://doi.org/10.1117/12.2613361
Event: SPIE Medical Imaging, 2022, San Diego, California, United States

Abstract

X-ray image segmentation of different anatomical structures or tissue types is essential for diagnosing lesions of various kinds and for the differentiation between contrast agent and bone tissue. However, the complete separation of multiple targets and tissue types remains a challenge. We describe the use a combination of high-dimensional data clustering and material decomposition methods using spectral information from an energy resolving CdTe Medipix3 photon-counting detector. This paper introduces a flexible, iterative semi-supervised algorithm for multi-material decomposition that uses spectral measurements and the K-edge effects to label and classify CT voxel clusters using a Gaussian Mixture Model (GMM). Preliminary results show excellent quantitative accuracy and separation of more than 3 materials. Results are shown with phantom and mouse CT data. Our correction and calibration methods required for these successful decomposition results will also be described.

Conference Presentation

Citation Download Citation

Juan C. R. Luna, Ian Harmon, and Mini Das "Tissue classification and contrast agent separation in spectral micro CT using Medipix3 CdTe detector", Proc. SPIE PC12031, Medical Imaging 2022: Physics of Medical Imaging, PC120310N (11 April 2022); https://doi.org/10.1117/12.2613361

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