| Project/Area Number |
14580821
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Single-year Grants |
|---|
| Section | 一般 |
|---|
| Research Field |
Biomedical engineering/Biological material science
|
|---|
| Research Institution | Yamaguchi University |
|---|
Principal Investigator |
KIDO Shoji Yamaguchi University, Faculty of Engineering, Professor, 工学部, 教授 (90314814)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
MATSUMOTO Tsuneo Yamaguchi University, Faculty of Medicine, Associate Professor, 医学部, 助教授 (70116755)
MATSUNAGA Naofumi Yamaguchi University, Faculty of Medicine, Professor, 医学部, 教授 (40157334)
|
|---|
| Project Period (FY) |
2002 – 2004
|
| Project Status |
Completed (Fiscal Year 2004)
|
| Budget Amount *help |
¥3,500,000 (Direct Cost: ¥3,500,000)
Fiscal Year 2004: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2003: ¥1,200,000 (Direct Cost: ¥1,200,000)
Fiscal Year 2002: ¥1,100,000 (Direct Cost: ¥1,100,000)
|
|---|
| Keywords | MDCT / Small pulmonary nodule / Temporal subtraction / Feature analysis / fractal / Computer-aided diagnosis / 肺腫瘤 / 支援診断 |
|---|
| Research Abstract |
The outline of our research results is summarized to the following four items :
1.Segmentation of small pulmonary nodules (SPNs)
Segmentation of SPNs on CT images accurately is an important technique for the feature characterization for differential diagnosis of SPNs. We have developed a computerized scheme for automatic segmentation of SPNs, and we can obtain precise volume data of SPNs, especially for GGO types.
2.Quantitative evaluation of temporal changes for SPNs
Quantitative evaluation of temporal changes for SPNs is an important for diagnosis of small lung cancers. We evaluated the doubling time of SPNs obtained from our computerized method, and we compared these results with findings reported by radiologists.
3.Feature analysis for the SPNs
Feature analysis of SPNs is an important for distinction between benign and malignant SPNs. The fractal dimension is a physical measure related to the complexity of object, and useful for feature analysis of SPNs. We analyzed the internal and peripheral textures of SPNs by use of fractal analysis for assisting radiologists' diagnoses.
4.Temporal subtraction of whole chest CT images
For the diagnosis of many kinds of lung diseases, we tried making of temporal subtraction for whole chest CT images. We used rib structures for this registration.
|
