Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction

Marcus Freyer; Angelique Ale; Ralf B. Schulz; Marta Zientkowska; Vasilis Ntziachristos; Karl-Hans Englmeier

doi:10.1117/1.3431101

1 May 2010 Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction

Marcus Freyer, Angelique Ale, Ralf B. Schulz, Marta Zientkowska, Vasilis Ntziachristos, Karl-Hans Englmeier

Author Affiliations +

Journal of Biomedical Optics, Vol. 15, Issue 3, 036006 (May 2010). https://doi.org/10.1117/1.3431101

Abstract

The recent development of hybrid imaging scanners that integrate fluorescence molecular tomography (FMT) and x-ray computed tomography (XCT) allows the utilization of x-ray information as image priors for improving optical tomography reconstruction. To fully capitalize on this capacity, we consider a framework for the automatic and fast detection of different anatomic structures in murine XCT images. To accurately differentiate between different structures such as bone, lung, and heart, a combination of image processing steps including thresholding, seed growing, and signal detection are found to offer optimal segmentation performance. The algorithm and its utilization in an inverse FMT scheme that uses priors is demonstrated on mouse images.

©(2010) Society of Photo-Optical Instrumentation Engineers (SPIE)

Citation Download Citation

Marcus Freyer, Angelique Ale, Ralf B. Schulz, Marta Zientkowska, Vasilis Ntziachristos, and Karl-Hans Englmeier "Fast automatic segmentation of anatomical structures in x-ray computed tomography images to improve fluorescence molecular tomography reconstruction," Journal of Biomedical Optics 15(3), 036006 (1 May 2010). https://doi.org/10.1117/1.3431101

Published: 1 May 2010

ACCESS THE FULL ARTICLE

JOURNAL ARTICLE
8 PAGES

DOWNLOAD PAPER SAVE TO MY LIBRARY