期刊
PATHOLOGY RESEARCH AND PRACTICE
卷 212, 期 10, 页码 927-936出版社
ELSEVIER GMBH
DOI: 10.1016/j.prp.2016.07.018
关键词
Image registration; Pathological image; Whole slide imaging; MR image; Optical image
类别
资金
- JSPS [25560189, 15H01105]
- National Institutes of Health [R01CA129371, K24CA125440A, K12CA090354]
- Grants-in-Aid for Scientific Research [25560189, 15H01105] Funding Source: KAKEN
Computed tomography (CT) and magnetic resonance (MR) imaging have been widely used for visualizing the inside of the human body. However, in many cases, pathological diagnosis is conducted through a biopsy or resection of an organ to evaluate the condition of tissues as definitive diagnosis. To provide more advanced information onto CT or MR image, it is necessary to reveal the relationship between tissue information and image signals. We propose a registration scheme for a set of PT images of divided specimens and a 3D-MR image by reference to an optical macro image (OM image) captured by an optical camera. We conducted a fundamental study using a resected human brain after the death of a brain cancer patient. We constructed two kinds of registration processes using the OM image as the base for both registrations to make conversion parameters between the PT and MR images. The aligned PT images had shapes similar to the OM image. On the other hand, the extracted cross-sectional MR image was similar to the OM image. From these resultant conversion parameters, the corresponding region on the PT image could be searched and displayed when an arbitrary pixel on the MR image was selected. The relationship between the PT and MR images of the whole brain can be analyzed using the proposed method. We confirmed that same regions between the PT and MR images could be searched and displayed using resultant information obtained by the proposed method. In terms of the accuracy of proposed method, the TREs were 0.56 +/- 0.39 mm and 0.87 +/- 0.42 mm. We can analyze the relationship between tissue information and MR signals using the proposed method. (C) 2016 The Authors. Published by Elsevier GmbH.
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