High Resolution Human Skin Image Segmentation by means of Fully Convolutional Neural Networks

被引：0

作者：

Calderon-Delgado, Manuel ^{[1
]}

Tjiu, Jeng-Wei ^{[2
]}

Lin, Ming-Yi ^{[2
]}

Huang, Sheng-Lung ^{[1
]}

机构：

[1] Natl Taiwan Univ, Grad Inst Photon & Optoelectrin, Taipei 10617, Taiwan

[2] Natl Taiwan Univ Hosp & Coll Med, Dept Dermatol, Taipei 100, Taiwan

来源：

2018 18TH INTERNATIONAL CONFERENCE ON NUMERICAL SIMULATION OF OPTOELECTRONIC DEVICES (NUSOD 2018) | 2018年

关键词：

optical coherence tomography; machine learning; convolutional neural networks; skin; medical imaging;

D O I：

暂无

中图分类号：

TM [电工技术]; TN [电子技术、通信技术];

学科分类号：

0808 ; 0809 ;

摘要：

Convolutional neural networks were applied to sub-micron-resolution optical coherence tomography images of the human skin for anatomical segmentation. The main layers of skin were discerned with an average 90% accuracy, which we believe to possess potential in the assessment of skin health.

引用

页码：31 / 32

页数：2

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