| Project/Area Number |
20790888
|
|---|
| Research Category |
Grant-in-Aid for Young Scientists (B)
|
| Allocation Type | Single-year Grants |
|---|
| Research Field |
Radiation science
|
|---|
| Research Institution | Gifu University |
|---|
Principal Investigator |
UCHIYAMA Yoshikazu Gifu University, 大学院・医学系研究科, 准教授 (50325172)
|
|---|
| Project Period (FY) |
2008 – 2009
|
| Project Status |
Completed (Fiscal Year 2009)
|
| Budget Amount *help |
¥2,210,000 (Direct Cost: ¥1,700,000、Indirect Cost: ¥510,000)
Fiscal Year 2009: ¥1,040,000 (Direct Cost: ¥800,000、Indirect Cost: ¥240,000)
Fiscal Year 2008: ¥1,170,000 (Direct Cost: ¥900,000、Indirect Cost: ¥270,000)
|
|---|
| Keywords | 医用画像工学 / コンピュータ支援診断 / ラクナ梗塞 / MR画像 / Magnetic Resonance Imaging |
|---|
| Research Abstract |
The detection of asymptomatic lacunar infarcts on MR images is important because their presence indicates an increased risk of severe cerebral infarction. However, accurate identification of lacunar infarcts is often hard for radiologists because of the difficulty in distinguishing lacunar infarcts and enlarged Virchow-Robin (VR) spaces. Thus, the purpose of this study was to develop a computer-aided diagnosis (CAD) scheme for the detection of lacunar infarcts. This study showed following useful results. (1) We developed a method for classification of lacunar infarcts and VR spaces. Image features, such as, size, shape, and signal intensity, were determined from the segmented lesions. A neural network with image features was employed for distinguishing between lacunar infarcts and enlarged VR spaces. The result obtained from 109 patients indicated that the area under the ROC curve was 0.945. (2) We developed a method for making a fusion image of T2-weighted image and MRA image. The blood flow obtained from MRA was superimposed on the lesion in T2-weighted image. Blood flow on the lesion was a crucial piece of information for the diagnosis of VR spaces. Our CAD scheme would be useful in assisting radiologists for the detection of lacunar infarcts in MR images.
|
