@inproceedings{d69e5e354eab4f6b902b6e48e91b5470,
title = "Construction of multimodal 3D model of pancreatic cancer tumor",
abstract = "Histopathological imaging and Magnetic Resonance (MR) are two equally important yet very distinct modalities of medical imaging. The high resolution of the first and the non-invasiveness of the later provide complementary information for medical diagnosis and research. Due to their largely different resolutions, the registration between 3D images of these two modalities is challenging. The objective of this paper is to create a multimodal 3D model of pancreatic cancer tumor by performing the registration of a reconstructed 3D pathological image and an MR image from a KPC mouse. The tumor portions were manually segmented and the 3D pathological image was reconstructed using landmark-based non-linear registration. The process starts by registering the outline of the images using the LDDMM non-linear registration method to match the binary labels of the tumor regions. Next, a non-linear B-spline deformation method based on mutual information maximization is used to register the internal structures of the images. Experimental results show that the overall shape of the tumor and its internal necrosis portion could be correctly registered, although the quality of the manual segmentations affects the accuracy of the registration.",
author = "Yushi Goto and Mauricio Kugler and Tatsuya Yokota and Chika Iwamoto and Kenoki Ohuchida and Makoto Hashizume and Hidekata Hontani",
note = "Funding Information: This study was partially supported by Grant-in-Aid for Scientific Research on Innovative Areas from the Ministry of Education, Culture, Sports, Science and Technology of Japan (26108003). Publisher Copyright: {\textcopyright} 2019 SPIE.; International Forum on Medical Imaging in Asia 2019 ; Conference date: 07-01-2019 Through 09-01-2019",
year = "2019",
doi = "10.1117/12.2521394",
language = "English",
series = "Proceedings of SPIE - The International Society for Optical Engineering",
publisher = "SPIE",
editor = "Feng Lin and Kim, {Jong Hyo} and Hiroshi Fujita",
booktitle = "International Forum on Medical Imaging in Asia 2019",
address = "United States",
}