Abstract
Constructing a mosaicing image with a broader field-of-view has become an important topic in image guided diagnosis and treatment. In this paper, we present a robust feature-based method for video mosaicing with super-resolution for optical medical images. Firstly, outliers involved in the feature dataset are removed using trilinear constraints and iterative bundle adjustment, then a minimal cost graph path is built for mosaicing using topology inference. Finally, a mosaicing image with super-resolution is created by way of maximum a posterior (MAP) estimation and selective initialization. The proposed method has been tested with both endoscopic images from totally endoscopic coronary artery bypass surgery and fibered confocal microscopy images. The results showed our method performs better than previously reported methods in terms of accuracy and robustness to deformation and artefacts.
This is a preview of subscription content, log in via an institution to check access.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
Similar content being viewed by others
References
Vercauteren, T., Perchant, A., Malandain, G., Pennec, X., Ayache, N.: Robust mosaicing with correction of motion distortions and tissue deformation for in vivo fibered microscopy. Medical Image Analysis 10(5), 673–692 (2006)
Miranda-Luna, R., Daul, C., Blondel, W.C.P.M., Hernandez-Mier, Y., Wolf, D., Guillemin, F.: Mosaicing of bladder endoscopic image sequences: distortion calibration and registration algorithm. IEEE Trans. on Biomed. Eng. 55, 541–553 (2008)
Can, A., Stewart, C.V., Roysam, B., Tanenbaum, H.L.: A feature-based, robust, hierarchical algorithm for registering pairs of images of the curved human retina. IEEE Trans. PAMI 24, 347–364 (2002)
Bay, H., Tuytelaars, T., Gool, L.V.: SURF: Speeded up robust features. In: Leonardis, A., Bischof, H., Pinz, A. (eds.) ECCV 2006. LNCS, vol. 3951, pp. 404–417. Springer, Heidelberg (2006)
Cattin, P.C., Bay, H., Van Gool, L., Szekely, G.: Retina Mosaicing Using Local Features. In: Larsen, R., Nielsen, M., Sporring, J. (eds.) MICCAI 2006. LNCS, vol. 4191, pp. 185–192. Springer, Heidelberg (2006)
Atasoy, S., Noonan, D., Benhimane, S., Navab, N., Yang, G.-Z.: A global approach for automatic fibroscopic video mosaicing in minimally invasive diagnosis. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part I. LNCS, vol. 5241, pp. 850–857. Springer, Heidelberg (2008)
Lerotic, M., Chung, A.J., Clark, J., Valibeik, S., Yang, G.Z.: Dynamic view expansion for enhanced navigation in Natural Orifice Transluminal Endoscopic Surgery. In: Metaxas, D., Axel, L., Fichtinger, G., Székely, G. (eds.) MICCAI 2008, Part II. LNCS, vol. 5242, pp. 467–475. Springer, Heidelberg (2008)
Mountney, P., Yang, G.Z.: Dynamic view expansion for minimally invasive surgery using simultaneous localization and mapping. Proc. IEEE Eng. Med. Biol. Soc., 1184–1187 (2009)
Brown, M., Lowe, D.G.: Automatic panoramic image stitching using invariant features. International Journal of Computer Vision 74, 59–73 (2007)
Lucas, B., Kanade, T.: An Iterative Image Registration Technique with an Application to Stereo Vision. In: Proc. IJCAI, pp. 674–679 (1981)
Baker, S., Matthews, I.: Lucas-Kanade 20 Years On: A Unifying Framework. International Journal of Computer Vision 56(3), 221–255 (2004)
Shashua, A.: Algebraic functions for recognition. IEEE Trans. PAMI 17(8), 779–789 (1995)
Fischler, M.A., Bolles, R.C.: Random Sample Consensus: A Paradigm for Model Fitting with Applications to Image Analysis and Automated Cartography. Comm. of the ACM 24, 381–395 (1981)
Sawhney, H.S., Hsu, S., Kumar, R.: Robust video mosaicing through topology inference and local to global alignment. In: Burkhardt, H., Neumann, B. (eds.) ECCV 1998. LNCS, vol. 1407, pp. 103–119. Springer, Heidelberg (1998)
Marzotto, R., Fusiello, A., Murino, V.: High resolution video mosaicing with global alignment. In: Proc. CVPR, pp. 692–698 (2004)
McLauchlan, P.F., Jaenicke, A.: Image mosaicing using sequential bundle adjustment. Image and Vision Computing 20, 751–759 (2002)
Capel, D.P.: Image Mosaicing and Super-Resolution, PhD thesis, Dept. of Eng. Science, Univ. of Oxford (2001)
Author information
Authors and Affiliations
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2010 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Hu, M. et al. (2010). A Robust Mosaicing Method with Super-Resolution for Optical Medical Images . In: Liao, H., Edwards, P.J."., Pan, X., Fan, Y., Yang, GZ. (eds) Medical Imaging and Augmented Reality. MIAR 2010. Lecture Notes in Computer Science, vol 6326. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15699-1_39
Download citation
DOI: https://doi.org/10.1007/978-3-642-15699-1_39
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-15698-4
Online ISBN: 978-3-642-15699-1
eBook Packages: Computer ScienceComputer Science (R0)