Registration of microscopic iris image sequences using probabilistic mesh

Authors:
Xubo B. Song;Andriy Myronenko;Stephen R. Plank;James T. Rosenbaum
Affiliations:
Department of Computer Science and Electrical Engineering, OGI School of Science and Engineering, Oregon Health and Science University;Department of Computer Science and Electrical Engineering, OGI School of Science and Engineering, Oregon Health and Science University;Department of Ophthalmology, Department of Cell and Developmental Biology, and Department of Medicine, Casey Eye Institute, Oregon Health and Science University;Department of Ophthalmology, Department of Cell and Developmental Biology, and Department of Medicine, Casey Eye Institute, Oregon Health and Science University
Venue:
MICCAI'06 Proceedings of the 9th international conference on Medical Image Computing and Computer-Assisted Intervention - Volume Part II
Year:
2006

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Abstract

This paper explores the use of deformable mesh for registration of microscopic iris image sequences. The registration, as an effort for stabilizing and rectifying images corrupted by motion artifacts, is a crucial step toward leukocyte tracking and motion characterization for the study of immune systems. The image sequences are characterized by locally nonlinear deformations, where an accurate analytical expression can not be derived through modeling of image formation. We generalize the existing deformable mesh and formulate it in a probabilistic framework, which allows us to conveniently introduce local image similarity measures, to model image dynamics and to maintain a well-defined mesh structure and smooth deformation through appropriate regularization. Experimental results demonstrate the effectiveness and accuracy of the algorithm.