A new approach of geodesic reconstruction for drusen segmentation in eye fundus images

Segmentation of bright blobs in an image is an important problem in computer vision and particularly in biomedical imaging. In retinal angiography, segmentation of drusen, a yellowish deposit located on the retina, is a serious challenge in proper diagnosis and prevention of further complications. Drusen extraction using classic segmentation methods does not lead to good results. We present a new segmentation method based on new transformations we introduced in mathematical morphology. It is based on the search for a new class of regional maxima components of the image. These maxima correspond to the regions inside the drusen. We present experimental results for drusen extraction using images containing examples having different types and shapes of drusen. We also apply our segmentation technique to two important cases of dynamic sequences of drusen images. The first case is for tracking the average gray level of a particular drusen in a sequence of angiographic images during a fluorescein exam. The second case is for registration and matching of two angiographic images from widely spaced exams in order to characterize the evolution of drusen.

[1]  Tony Lindeberg,et al.  Scale-Space Theory in Computer Vision , 1993, Lecture Notes in Computer Science.

[2]  Corinne Vachier.  Extraction de caractéristiques, segmentation d'image et morphologie mathématique , 1995 .

[3]  Demetri Terzopoulos,et al.  Deformable models in medical image analysis: a survey , 1996, Medical Image Anal..

[4]  Max A. Viergever,et al.  A survey of medical image registration , 1998, Medical Image Anal..

[5]  Benjamin B. Kimia,et al.  Image segmentation by reaction-diffusion bubbles , 1995, Proceedings of IEEE International Conference on Computer Vision.

[6]  Laurent D. Cohen,et al.  Finite-Element Methods for Active Contour Models and Balloons for 2-D and 3-D Images , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[7]  Laurent D. Cohen,et al.  On active contour models and balloons , 1991, CVGIP Image Underst..

[8]  M. Grimaud.  La geodesie numerique en morphologie mathematique. Application a la detection des microcalcifications en mammographie numerique , 1991 .

[9]  Luc Vincent,et al.  Morphological Area Openings and Closings for Grey-scale Images , 1994 .

[10]  Jean Serra,et al.  Image Analysis and Mathematical Morphology , 1983 .

[11]  R W Young,et al.  Pathophysiology of age-related macular degeneration. , 1987, Survey of ophthalmology.

[12]  Laurent D. Cohen,et al.  A new approach for geodesic reconstruction in mathematical moprphology and application to image segmentation and tracking in ophtalmology , 2001 .

[13]  Baba C. Vemuri,et al.  Shape Modeling with Front Propagation: A Level Set Approach , 1995, IEEE Trans. Pattern Anal. Mach. Intell..

[14]  Michel Grimaud,et al.  New measure of contrast: the dynamics , 1992, Optics & Photonics.

[15]  Luc Vincent,et al.  Watersheds in Digital Spaces: An Efficient Algorithm Based on Immersion Simulations , 1991, IEEE Trans. Pattern Anal. Mach. Intell..

[16]  Luc Vincent,et al.  Morphological grayscale reconstruction in image analysis: applications and efficient algorithms , 1993, IEEE Trans. Image Process..

[17]  W R Green,et al.  Pathologic Features of Senile Macular Degeneration , 1985, Ophthalmology.

[18]  V. Caselles,et al.  A geometric model for active contours in image processing , 1993 .

[19]  Frederic Fol Leymarie,et al.  Tracking Deformable Objects in the Plane Using an Active Contour Model , 1993, IEEE Trans. Pattern Anal. Mach. Intell..

[20]  M. Killingsworth,et al.  Softening of drusen and subretinal neovascularization. , 1980, Transactions of the ophthalmological societies of the United Kingdom.

[21]  K R Kenyon,et al.  Diffuse drusen and associated complications. , 1985, American journal of ophthalmology.

[22]  Laurent Najman,et al.  Geodesic Saliency of Watershed Contours and Hierarchical Segmentation , 1996, IEEE Trans. Pattern Anal. Mach. Intell..

[23]  John F. Canny,et al.  A Computational Approach to Edge Detection , 1986, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[24]  Marie-Odile Berger,et al.  Recalage automatique d'images d'angiographie , 1999 .

[25]  Rangachar Kasturi,et al.  Machine vision , 1995 .