Development of a computerized system for analyzing facial nerve paralysis -A method using the optical flow-
| Project/Area Number |
12671681
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| Research Category |
Grant-in-Aid for Scientific Research (C)
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| Allocation Type | Single-year Grants |
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| Section | 一般 |
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| Research Field |
Otorhinolaryngology
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| Research Institution | Keio University |
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Principal Investigator |
KUNIHIRO Takanobu Keio University, School of Medicine, Assistant Professor, 医学部, 専任講師 (10170010)
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| Co-Investigator(Kenkyū-buntansha) |
白石 清嗣 飛鳥インターナショナル株式会社, 研究員
KANZAKI Jin Keio University, School of Medicine, Professor, 医学部, 教授 (00051441)
MINAMITANI Haruyuki Keio University, Faculty of Science and Technology, Professor, 医学部, 専任講師 (70051779)
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| Project Period (FY) |
2000 – 2001
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| Project Status |
Completed (Fiscal Year 2001)
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| Budget Amount *help |
¥3,800,000 (Direct Cost: ¥3,800,000)
Fiscal Year 2001: ¥1,400,000 (Direct Cost: ¥1,400,000)
Fiscal Year 2000: ¥2,400,000 (Direct Cost: ¥2,400,000)
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| Keywords | facial nerve palsy / objective assessment / optical flow / computer / gradient method / 評価法 |
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| Research Abstract |
We developed a computerized system to assess the degree of facial nerve paralysis. Our system calculates the optical flow throughout the facial area, using the gradient method.
The results obtained with our system were both precise and reproducible. They were almost identical to those obtained using the matching method, and the inter-examiner variability was minimal. In addition, when expressed using the diseased-to-healthy side ratio of the optical flow, the results correlated well with the scores assigned to each facial movement using Yanagihara's grading scale. The optical flow index, which we defined using the results, is also highly correlated with the total scores on Yanagihara's grading scale.
Another advantage of our system is that it permits flexible expression of the analysis results. For example, the optical flow for each small area within the facial region can be superimposed on the original picture of the patient. This enables intuitive understanding of the facial movements. Furthermore, the movement of each pixel in the facial region can be traced on a frame-to-frame basis. These two features are very useful for assessing associated movements.
Our system initially ran only on Linux, but it now also works on Windows. We expect that our system will be used widely in daily clinical practice.
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Report
(3 results)
Research Products
(13 results)
