2002 Fiscal Year Final Research Report Summary
Basic Research for the Development of Helical Cone-Beam CT
| Project/Area Number |
13650452
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Measurement engineering
|
|---|
| Research Institution | University of Tsukuba |
|---|
Principal Investigator |
KUDO Hiroyuki University of Tsukuba Information Sciences and Electronics, Associate Professor, 電子・情報工学系, 助教授 (60221933)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
MURAYAMA Hideo National Institute of Radiological Sciences, Division of Medical Physics, Head of Diagnostic System Group, 医学物理部, 診断システム開発室長 (50166310)
|
|---|
| Project Period (FY) |
2001 – 2002
|
| Keywords | CT / Cone-Beam / Image Reconstruction / Angiography / Micro CT / Helical / Medical Imaging / Image Processing |
|---|
| Research Abstract |
Cone-beam helical CT (based on combining the cone-beam x-ray exposure and the helical scanning) is receiving increased attention as a future fast 3-D CT. However, enough basic researches are not performed in the current stage about its scanner design and image reconstruction. The aim of this research project is to investigate the following three points which are important to develop helical cone-beam CT scanners. First, we developed an efficient scanner design method which is based on arranging detector elements very efficiently. This allows us to scan the patient with a large (maximum) helical pitch even in the case where the number of detector elements are limited. Next, we developed the following two types of image reconstruction methods. The first type aims at using in commercial helical cone-beam CT scanners. These include an exact algorithm based on the 3-D Radon inversion and an approximate (but very fast) algorithm based on rebinning cone-beam data into fan-beam data. The second type aims at using in angiography and micro-CT systems. The algorithm is an algebraic one which is based on the duality of non-linear programming. During the. development of these algorithms, we also obtained two important insights about basic mathematics of CT image reconstruction. These include a super-short-scan image reconstruction and a new exact cone-beam reconstruction method for general source trajectory. Finally, as an application to real data, we applied the developed algebraic reconstruction algorithm to the micro-CT system at Marquette university. The result demonstrates that it is possible to reconstruct a high-quality 3-D image of a rat lung (confined within a cube of side 2cm) from only 8 projections with the developed algorithm.
|
