| Project/Area Number |
11650380
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
情報通信工学
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| Research Institution | Osaka University |
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Principal Investigator |
IIGUNI Youji Graduate School of Engineering, Osaka University Associate Professor, 大学院・工学研究科, 助教授 (80168054)
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| Project Period (FY) |
1999 – 2001
|
| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2001: ¥800,000 (Direct Cost: ¥800,000)
Fiscal Year 2000: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 1999: ¥1,500,000 (Direct Cost: ¥1,500,000)
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| Keywords | 3D medical image data / Kronecker product / hierarchical coding / regularization theory / cross section display / radial basis function / 動経基底関数 |
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| Research Abstract |
A hierarchical coding algorithm for 3D medical images based upon hierarchical interpolation with radial basis function networks is proposed. By using the properties of Kronecker product, the computation of the network parameters and the 3D image reconstruction are efficiently done in O(L^4) computation time and O(L^3) storage space, when applied to 3D images of size (L x L x L). A further reduction of processing time is accomplished by using sparse matrix techniques. The salient features of the proposed coding method are that arbitrary cross section images can be progressively displayed without reconstructing the whole 3D image, the first image reconstruction starts as soon as the first data transmission has been completed, no expanding procedure is required in 3D image reconstruction, and the blocking effects are not apparent even in the lowest resolution image. Experimental results using two 3D MRI images of size (128 x 128 x 64) with 8-bit gray levels show that the coding performance is better than that of the 3D DOT coding by about 0.25 bits/pixel at higher bitrates, and that the new cross section display method synthesizes the coarsest (finest) section image about six (three) times faster than the standard method that requires the whole 3D image reconstruction.
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