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Proceedings Paper

Thrombus segmentation by texture dynamics from microscopic image sequences
Author(s): Nicolas Brieu; Jovana Serbanovic-Canic; Ana Cvejic; Derek Stemple; Willem Ouwehand; Nassir Navab; Martin Groher
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Paper Abstract

The genetic factors of thrombosis are commonly explored by microscopically imaging the coagulation of blood cells induced by injuring a vessel of mice or of zebrafish mutants. The latter species is particularly interesting since skin transparency permits to non-invasively acquire microscopic images of the scene with a CCD camera and to estimate the parameters characterizing the thrombus development. These parameters are currently determined by manual outlining, which is both error prone and extremely time consuming. Even though a technique for automatic thrombus extraction would be highly valuable for gene analysts, little work can be found, which is mainly due to very low image contrast and spurious structures. In this work, we propose to semi-automatically segment the thrombus over time from microscopic image sequences of wild-type zebrafish larvae. To compensate the lack of valuable spatial information, our main idea consists of exploiting the temporal information by modeling the variations of the pixel intensities over successive temporal windows with a linear Markov-based dynamic texture formalization. We then derive an image from the estimated model parameters, which represents the probability of a pixel to belong to the thrombus. We employ this probability image to accurately estimate the thrombus position via an active contour segmentation incorporating also prior and spatial information of the underlying intensity images. The performance of our approach is tested on three microscopic image sequences. We show that the thrombus is accurately tracked over time in each sequence if the respective parameters controlling prior influence and contour stiffness are correctly chosen.

Paper Details

Date Published: 12 March 2010
PDF: 8 pages
Proc. SPIE 7623, Medical Imaging 2010: Image Processing, 76233Z (12 March 2010); doi: 10.1117/12.844230
Show Author Affiliations
Nicolas Brieu, Technische Univ. München (Germany)
Jovana Serbanovic-Canic, Wellcome Trust Sanger Institute (United Kingdom)
Ana Cvejic, Wellcome Trust Sanger Institute (United Kingdom)
Univ. of Cambridge (United Kingdom)
Derek Stemple, Wellcome Trust Sanger Institute (United Kingdom)
Univ. of Cambridge (United Kingdom)
Willem Ouwehand, Wellcome Trust Sanger Institute (United Kingdom)
Univ. of Cambridge (United Kingdom)
National Health Service Blood and Transplant (United Kingdom)
Nassir Navab, Technische Univ. München (Germany)
Martin Groher, Technische Univ. München (Germany)

Published in SPIE Proceedings Vol. 7623:
Medical Imaging 2010: Image Processing
Benoit M. Dawant; David R. Haynor, Editor(s)

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