6 March 2018 Landmark-based reconstruction of 3D smooth structures from serial histological sections
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Abstract
Given microscope images, one can observe 2D cross-sections of 3D micro anatomical structures with high spatial resolutions. Each of the 2D microscope images alone is, though, not suitable for studying the 3D anatomical structures and hence many works have been done on a 3D image reconstruction from a given series of microscope images of histological sections obtained from a single target tissue. For the 3D image reconstruction, an image registration technique is necessary because there exists the independent translation, rotation, and non-rigid deformation of the histological sections. In this paper, a landmark-based method of fully non-rigid image registration for the 3D image reconstruction is proposed. The proposed method first detects landmarks corresponded between given images by using a template matching and then non-rigidly deforms the images so that the corresponding landmarks detected in different images are located along a single smooth curve in the reconstructed 3D image. Most of all conventional methods for the reconstruction of 3D microscope image registers two consecutive images at a time and many micro anatomical structures often have unnatural straight shape along the vertical (z) direction in the resultant 3D image because, roughly speaking, the conventional methods registers two given images so that pixels with the same coordinates in the two images have the same pixel value. The proposed method, on the other hand, determine the deformations of all given images by referring to the all images and deforms them simultaneously. In the experiments, a 3D microscope image of the pancreas of a KPC mouse was reconstructed from a series of microscope images of the histological sections.
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Naoki Kawamura, Hirokazu Kobayashi, Tatsuya Yokota, Hidekata Hontani, Chika Iwamoto, Kenoki Ohuchida, Makoto Hashizume, "Landmark-based reconstruction of 3D smooth structures from serial histological sections", Proc. SPIE 10581, Medical Imaging 2018: Digital Pathology, 105811E (6 March 2018); doi: 10.1117/12.2293510; https://doi.org/10.1117/12.2293510
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