| Project/Area Number |
15300059
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (B)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Perception information processing/Intelligent robotics
|
|---|
| Research Institution | Osaka University |
|---|
Principal Investigator |
SATO Yoshinobu Osaka University, Graduate School of Medicine, Associate Professor, 医学系研究科, 助教授 (70243219)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
TAMURA Shinichi Osaka University, Graduate School of Medicine, Professor, 医学系研究科, 教授 (30029540)
JOHKOH Takeshi Osaka University, Graduate School of Medicine, Professor, 医学系研究科, 教授 (20263270)
NISHII Takashi Osaka University, Graduate School of Medicine, Assistant, 医学系研究科, 助手 (70304061)
HORI Masatoshi Osaka University, Graduate School of Medicine, Assistant, 医学系研究科, 助手 (00346206)
|
|---|
| Project Period (FY) |
2003 – 2005
|
| Project Status |
Completed (Fiscal Year 2005)
|
| Budget Amount *help |
¥14,600,000 (Direct Cost: ¥14,600,000)
Fiscal Year 2005: ¥2,700,000 (Direct Cost: ¥2,700,000)
Fiscal Year 2004: ¥4,100,000 (Direct Cost: ¥4,100,000)
Fiscal Year 2003: ¥7,800,000 (Direct Cost: ¥7,800,000)
|
|---|
| Keywords | ridge line extraction / ridge plane extraction / vessel extraction / vessel tracking / branch analysis / multiscale filter / multiorientation filter / scale space / 3次元画像 / 画像計測 / 等方性解像度 / 点広がり関数 / 多重解像度解析 / ヘッセ行列 / 血管 / 肺胞 / 多重スケール法 / 関節軟骨 / 3次元医用画像 / 精密定量化 / 3次元モデリング / 精度解析 / 超解像度 |
|---|
| Research Abstract |
Accurate quantification incorporating imaging conditions and uncertainty analysis
The measurement error of the sheet width due to limited resolution of the imaging processes and blurring involved in edge detection was theoretically analyzed. Measuring the thickness of sheet-like (or plate-like) anatomical structures, such as articular cartilages and brain cortex, in 3D magnetic resonance (MR) images is often an important diagnostic procedure. The purpose of this paper is to investigate the fundamental limits to the accuracy of thickness determination in MR images. Given imaging and postprocessing parameters, the characteristics of thickness determination accuracy are derived by means of a theoretical simulation method, focusing especially on the effect of sheet structure orientation on accuracy in the case of noncubic (anisotropic) voxels. The theoretical simulation was validated by in vitro experiments.
The effects of the PSF were incorporated into the width measurement procedure by for
… More
mulating it by an inverse problem. A method fully utilizes multiscale line filter responses to estimate the PSF of a scanner and diameters of small tubular structures based on the PSF. The estimation problem is formulated as a least square fitting of a sequence of multiscale responses obtained at each medial axis point to the precomputed multiscale response curve for the ideal line model. The method was validated through phantom experiments and demonstrated to `accurately measure small-diameter structures which are significantly overestimated by conventional methods based on the full width half maximum (FWHM) and zero-crossing edge detection.
Extraction of branching tubular structures
We develop a branch detector using multi-orientation analysis, which is especially effective for peripheral vessels under low contrast conditions. We integrate the proposed branch detector into a hybrid vessel tracking system, which adaptively selects two different mechanisms of branch detectors based on contrast evaluations by analyzing local intensity distribution. The proposed branch detector is used in low contrast case while a conventional method based on region growing in high contrast case. The hybrid tracking system copes with both of the stability in high contrast case and the robustness in low contrast case. The proposed method was shown to be effective through ROC analysis using abdominal CT data sets. We also showed that the proposed method could extract 90% of hepatic arteries observable by a radiologist in the cross-sectional images using 19 abdominal CT data sets. Less
|
