Accurate registration of in vivo time-lapse images

Seyed M. M. Kahaki; Shih-Luen Wang; Armen Stepanyants

doi:10.1117/12.2512257

15 March 2019 Accurate registration of in vivo time-lapse images

Seyed M. M. Kahaki, Shih-Luen Wang, Armen Stepanyants

Proceedings Volume 10949, Medical Imaging 2019: Image Processing; 109491D (2019) https://doi.org/10.1117/12.2512257
Event: SPIE Medical Imaging, 2019, San Diego, California, United States

Abstract

In vivo imaging experiments often require automated detection and tracking of changes in the specimen. These tasks can be hindered by variations in the position and orientation of the specimen relative to the microscope, as well as by linear and nonlinear tissue deformations. We propose a feature-based registration method, coupled with optimal transformations, designed to address these problems in 3D time-lapse microscopy images. Features are detected as local regions of maximum intensity in source and target image stacks, and their bipartite intensity dissimilarity matrix is used as an input to the Hungarian algorithm to establish initial correspondences. A random sampling refinement method is employed to eliminate outliers, and the resulting set of corresponding features is used to determine an optimal translation, rigid, affine, or B-spline transformation for the registration of the source and target images. Accuracy of the proposed algorithm was tested on fluorescently labeled axons imaged over a 68-day period with a two-photon laser scanning microscope. To that end, multiple axons in individual stacks of images were traced semi-manually and optimized in 3D, and the distances between the corresponding traces were measured before and after the registration. The results show that there is a progressive improvement in the registration accuracy with increasing complexity of the transformations. In particular, sub-micrometer accuracy (2-3 voxels) was achieved with the regularized affine and Bspline transformations.

Conference Presentation

Citation Download Citation

Seyed M. M. Kahaki, Shih-Luen Wang, and Armen Stepanyants "Accurate registration of in vivo time-lapse images", Proc. SPIE 10949, Medical Imaging 2019: Image Processing, 109491D (15 March 2019); https://doi.org/10.1117/12.2512257

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