1994 Fiscal Year Final Research Report Summary
The Analysis for 3 Dimensional Structure of Pulmonary Acinus ; the Approach for the Model on Computer Graphics.
| Project/Area Number |
05404038
|
|---|
| Research Category |
Grant-in-Aid for General Scientific Research (A)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Radiation science
|
|---|
| Research Institution | Osaka University |
|---|
Principal Investigator |
IKEZOE Jumpei Osaka University, Radiology, Associate Professor, 医学部, 助教授 (70115989)
|
|---|
| Co-Investigator(Kenkyū-buntansha) |
KONDOH Hiroshi Osaka University, Radiology, Associate Professor, 医学部, 助手 (70186857)
ARISAWA Jun Osaka University, Radiology, Associate Professor, 医学部, 助教授 (40144513)
NAITOH Hiroaki Osaka University, Radiology, Associate Professor, 医学部, 助教授 (60217627)
|
|---|
| Project Period (FY) |
1993 – 1994
|
| Keywords | high-resolution CT / intralobular reticular opacity / perilobular opacity / spared lobule / image analysis / Wavelet transformation / Laplacian-Gaussian filter / fractal analysis |
|---|
| Research Abstract |
The results of this research were composed of two parts as follows.
1. Radiologic-Pathologic Correlation.
At first, we proved the intralobular reticular opacity on high-resolution CT was made by not only interstitial cange but also alveolar filling process. In addition that, we found that the net of reticular opacity located in periaciner area. Next, perilobular opacity on high-resolution CT was able to be composed just of perilobular alveolar abnormality. Finally, we proved that spared lobule on high-resolution CT had the same pathologic findings as its surrounding abnormal lesions. This phenomenon was caused by the difference of disease profusion, the difference of drainage, and the difference of time.
2. Image Analysis by Computers.
At first, we applied the Wavelet Transformation to image compression of chest radiographs. This method may be available in clinical practice. Next, we established image analyzing system for interstitial lung abnormalities by using Laplacian-Gaussian filter and showed the usefulness and limitation of this method. Finally, we applied the fractal analysis to both chest radiographs and high-resolution CT images and obtained hopeful results.
|
