Abstract
This paper presents an automatic approach for measurement of the superficial spreading depth of cutaneous melanomas based on microscopic hyperspectral imaging technology. To extract the skin granular layer, an edge detection method combined with kernel minimum noise fraction is proposed. Then least squares support vector machine based on characteristic spectrum supervision is used to identify malignant melanocytes. The measurement of tumor superficial spreading depth depends on the vertical distance from the skin granular layer to the deepest malignant melanocytes. Experimental results illustrate that the proposed method is possible to provide an effective reference for the diagnosis and treatment of cutaneous melanoma.
| Translated title of the contribution | 显微高光谱成像的皮肤黑色素瘤浅表扩散深度识别方法 |
|---|---|
| Original language | English |
| Pages (from-to) | 749-759 |
| Number of pages | 11 |
| Journal | Hongwai Yu Haomibo Xuebao/Journal of Infrared and Millimeter Waves |
| Volume | 39 |
| Issue number | 6 |
| DOIs | |
| State | Published - Dec 2020 |
Keywords
- Image processing
- Machine learning
- Microscopic hyperspectral imaging
- Superficial spreading depth