1995 Fiscal Year Final Research Report Summary
Study of 3D Shape Reconstruction from Medical and Industrial Endoscope Images
| Project/Area Number |
06555117
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| Research Category |
Grant-in-Aid for Developmental Scientific Research (B)
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| Allocation Type | Single-year Grants |
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| Research Field |
計測・制御工学
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| Research Institution | University of Tokyo |
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Principal Investigator |
DEGUCHI Koichiro Univ.of Tokyo, Faculty of Eng., Assoc.Professor, 大学院・工学系研究科, 助教授 (30107544)
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| Co-Investigator(Kenkyū-buntansha) |
NAGAMATSU Leo Univ.of Tokyo, Faculty of Eng., Research Associate, 大学院・工学系研究科, 助手 (40172556)
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| Project Period (FY) |
1994 – 1995
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| Keywords | Imaga Processing / Imaga Measurement / Endoscope / Shape Recongnition / Medical Image Analysis / Computer Vision |
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| Research Abstract |
In this research, we established a methodology for 3-dimensional shape reconstruction from Medical and Industrial Endoscope Images, and constructed experimental system to verify its performances.
The main works were development of next two new method :
1.A new application of the factorization method for 3-D shape reconstruction from endoscope image sequences.
This method achieves high accuracy of shape reconstruction by using a large number of points and images, and robustly applying a well-understood matrix computations. We admitted that this method was easy to understand, easy to implement, and providing enough accuracy for the case where the approximation on the optical system holds well.However, the latter half process of the method, named normalization, was not so wellunderstandable as the use of singular value decomposition in its first half. Then, in this study, we reconstructed the detail theoretical basis and inproved the feasibility of actual use for medical applications
2.Reconstructing a shape from it's shaded image in the case where a point light source is at the projection center. This condition well approximates the imaging system of an endoscope. In this case, the image gray level depends on not only the gradient of the object surface but also the distance from the light source to each point on the surface. To deal with this difficulty, we introduce the evolution equation for equal-range contours on the surface. Propagating this contour by solving the equation, we can reconstruct a shape. Experimental results for real medical endoscope images of a human stomach inner wall show feasibility of this method, and present a promising technique for morphological analysis of tumors on human inner organs.
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