Abstract
It is well known that an earlobe crease (ELC) is related with cardiovascular disease. However evaluation of ELC has been carried out subjectively. We propose a novel system for objective and quantitative evaluation of ELC characteristics. The outline of earlobe was detected using the Canny edge detector. The number of ELCs and the ratio of the ELC length for the lobule from photographs of bilateral earlobes were calculated from the extracted outline of earlobes. Our system's validity for ELCs detection was compared with doctors' diagnosis using sensitivity and specificity analysis. The result showed that the validity of our system was equal to the diagnosis of the medical doctors (kappa coefficient: 0.93). It was thus concluded that the proposed system is useful to predict atherosclerotic disease.
| Original language | English |
|---|---|
| Title of host publication | 2016 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 |
| Publisher | Institute of Electrical and Electronics Engineers Inc. |
| Pages | 2374-2377 |
| Number of pages | 4 |
| ISBN (Electronic) | 9781457702204 |
| DOIs | |
| Publication status | Published - 13-10-2016 |
| Externally published | Yes |
| Event | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 - Orlando, United States Duration: 16-08-2016 → 20-08-2016 |
Publication series
| Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
|---|---|
| Volume | 2016-October |
| ISSN (Print) | 1557-170X |
Other
| Other | 38th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2016 |
|---|---|
| Country/Territory | United States |
| City | Orlando |
| Period | 16-08-16 → 20-08-16 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
All Science Journal Classification (ASJC) codes
- Signal Processing
- Biomedical Engineering
- Computer Vision and Pattern Recognition
- Health Informatics
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