Reliable melanoma discrimination system offers grounds of the decision
| Project/Area Number |
26461666
|
|---|
| Research Category |
Grant-in-Aid for Scientific Research (C)
|
| Allocation Type | Multi-year Fund |
|---|
| Section | 一般 |
|---|
| Research Field |
Dermatology
|
|---|
| Research Institution | Hosei University |
|---|
Principal Investigator |
|
|---|
| Project Period (FY) |
2014-04-01 – 2017-03-31
|
| Project Status |
Completed (Fiscal Year 2016)
|
| Budget Amount *help |
¥4,940,000 (Direct Cost: ¥3,800,000、Indirect Cost: ¥1,140,000)
Fiscal Year 2016: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2015: ¥1,430,000 (Direct Cost: ¥1,100,000、Indirect Cost: ¥330,000)
Fiscal Year 2014: ¥2,080,000 (Direct Cost: ¥1,600,000、Indirect Cost: ¥480,000)
|
|---|
| Keywords | 自動診断支援 / メラノーマ / 深層学習 / 画像解析 / 機械学習 / 自動診断 / deep learning / 画像診断 |
|---|
| Outline of Final Research Achievements |
We have investigated to build a reliable melanoma discrimination system capable of providing grounds for the decision. Our model successfully estimates all items defined in commonly used clinical findings for melanoma, i.e. a total 15 items defined in ABCD rule and 7-point checklist. We also developed efficient pre-processing techniques for melanoma discrimination for deep learning approach. Our method reduced time-consuming training time to less than 1/9, but it attained superior performance in discriminating melanomas to expert dermatologists.
|
Report
(4 results)
Research Products
(19 results)
