2007 Fiscal Year Final Research Report Summary
Intelligent CAD Based on Quantitative Analysis of Spatio-Temporal Change in Medical Image Sequence
| Project/Area Number |
15070206
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| Research Category |
Grant-in-Aid for Scientific Research on Priority Areas
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| Allocation Type | Single-year Grants |
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| Review Section |
Science and Engineering
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| Research Institution | Kyoto University |
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Principal Investigator |
SUGIMOTO Naozo Kyoto University, Graduate School of Informatics, Associate Professor (20196752)
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| Co-Investigator(Kenkyū-buntansha) |
EIHO Shigeru Kyoto College of Graduate Studies of Informatics, Professor (40026117)
SEKIGUCHI Hiroyuki Kyoto University, Graduate School of Informatics, Assistant Professor (90243063)
MATSUDA Tetsuya Kyoto University, Graduate School of Informatics, Professor (00209561)
MIZUTA Shinobu Kyoto University, Graduate School of Informatics, Assistant Professor (40314265)
URAYAMA Shin-ichi Kyoto University, Graduate School of Medicine, Assistant Professor (10270729)
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| Project Period (FY) |
2003 – 2006
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| Keywords | Medical Image Processig / CAD / Cardiac Imaging / Multi Dimensional Image / Image Sequences / Rapid Imaging / Image Registration |
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| Research Abstract |
Our challenge is to develop an intelligent computer aided diagnosis (CAD) systems based on quantitative analysis of spatio-temporal change in high resolution multidimensional image sequence. We also focused on imaging and image processing of 4d images and on image database system for aiding observing sequential multidimensional images. Although we should develop a lot of techniques to achieve our purpose, we could not do everything in the restricted period of the projects and we, then, mainly focused on the following three systems and obtained results.
1. CAD for analyzing cardiac function by using 4d MR tagging images (1) We developed retrospective cardiac-respiratory dual gating system for MR tagging. Obtained data were corrected and reconstructed by our newly developed k-t interpolation method. We also developed transient artifact free 4d tagging sequence by using TARD and LISA technique. (2) We developed a new tag detection and analysis method in 5d (x, y, z, t, I) space. (3) About 100 data set of high resolution 4d chest MRI were obtained.
2. Sequential 3d image database and its data retrieval and displaying system of human embryos (1) We developed prototype system, and it was found that the system was useful for observing difference between subjects or between different growing stages. It seems that concept of this system can be used for CAD system for diagnosing image sequence. (2) We developed a new multidimensional image description method (RBCT), and it was useful for segmentation and displaying of multidimensional images.
3. CAD system for aortic change in 3d X-ray CT images
We developed CAD for observing aortic change. The system has functions of segmenting aortic region, detecting calcification region around aorta, and measuring several parameters (aortic diameter, number and volume of calcification region, and so on). The system was implemented as a plug-in system for PLUTO.
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Research Products
(34 results)
