Abstract
Curvilinear structures are common in medical imaging, which typically require dedicated processing techniques. We present a new structure to process these, that we call the polygonal path image, denoted \(\mathfrak{P}\). We derive from \(\mathfrak{P}\) some curvilinear structure enhancement and analysis algorithms. We show that \(\mathfrak{P}\) has some interesting properties: it generalizes several concepts found in other methods; it makes it possible to control the smoothness and length of the structures under study; and it can be computed efficiently. We estimate quantitatively its performance in the context of interventional cardiology for the detection of guide-wires in X-ray images. We show that \(\mathfrak{P}\) is particularly well suited for this task where it appears to outperform previous state of the art techniques.
Keywords
- curvilinear structures
- image segmentation
- shortest path
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Franken, E., Rongen, P., van Almsick, M., ter Haar Romeny, B.M.: Detection of Electrophysiology Catheters in Noisy Fluoroscopy Images. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 25–32. Springer, Heidelberg (2006)
Bismuth, V., Vancamberg, L., Gorges, S.: A comparison of line enhancement techniques: applications to guide-wire detection and respiratory motion tracking. SPIE Conference Series, vol. 7259 (2009)
Barbu, A., Athitsos, V., Georgescu, B., Boehm, S., Durlak, P., Comaniciu, D.: Hierarchical learning of curves application to guidewire localization in fluoroscopy. In: Proc. CVPR, pp. 1–8. IEEE (2007)
Honnorat, N., Vaillant, R., Paragios, N.: Guide-Wire Extraction through Perceptual Organization of Local Segments in Fluoroscopic Images. In: Jiang, T., Navab, N., Pluim, J.P.W., Viergever, M.A. (eds.) MICCAI 2010, Part III. LNCS, vol. 6363, pp. 440–448. Springer, Heidelberg (2010)
Frangi, A.F., Niessen, W.J., Vincken, K.L., Viergever, M.A.: Multiscale Vessel Enhancement Filtering. In: Wells, W.M., Colchester, A.C.F., Delp, S.L. (eds.) MICCAI 1998. LNCS, vol. 1496, pp. 130–137. Springer, Heidelberg (1998)
Meijering, E., Jacob, M., Sarria, J., Steiner, P., Hirling, H., Unser, M.: Design and validation of a tool for neurite tracing and analysis in fluorescence microscopy images. Cytometry Part A 58(2), 167–176 (2004)
Vincent, L.: Minimal path algorithms for the robust detection of linear features in gray images. In: Proc. ISMM, pp. 331–338. Kluwer Acad. (1998)
Rouchdy, Y., Cohen, L.: Image segmentation by geodesic voting. application to the extraction of tree structures from confocal microscope images. In: ICPR 2008, pp. 1–5. IEEE (2008)
Carlotto, M.J.: Enhancement of low-contrast curvilinear features in imagery. IEEE Transactions on Image Processing 16(1), 221–228 (2007)
Tankyevych, O.: Filtering of thin objects: applications to vascular image analysis. PhD thesis, Université Paris Est (2010)
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Bismuth, V., Vaillant, R., Talbot, H., Najman, L. (2012). Curvilinear Structure Enhancement with the Polygonal Path Image - Application to Guide-Wire Segmentation in X-Ray Fluoroscopy. In: Ayache, N., Delingette, H., Golland, P., Mori, K. (eds) Medical Image Computing and Computer-Assisted Intervention – MICCAI 2012. MICCAI 2012. Lecture Notes in Computer Science, vol 7511. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-33418-4_2
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DOI: https://doi.org/10.1007/978-3-642-33418-4_2
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-33417-7
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