التفاصيل البيبلوغرافية
| العنوان: |
Computer-Aided Detection (CADe) System with Optical Coherent Tomography for Melanin Morphology Quantification in Melasma Patients |
| المؤلفون: |
I-Ling Chen, Yen-Jen Wang, Chang-Cheng Chang, Yu-Hung Wu, Chih-Wei Lu, Jia-Wei Shen, Ling Huang, Bor-Shyh Lin, Hsiu-Mei Chiang |
| المصدر: |
Diagnostics; Volume 11; Issue 8; Pages: 1498 |
| بيانات النشر: |
Multidisciplinary Digital Publishing Institute |
| سنة النشر: |
2021 |
| المجموعة: |
MDPI Open Access Publishing |
| مصطلحات موضوعية: |
melasma, melanin, optical coherence tomography, cellular resolution, full-field OCT, photoaging, deep learning, image denoising, convolutional neural networks, computer-aided detection |
| الوصف: |
Dark skin-type individuals have a greater tendency to have pigmentary disorders, among which melasma is especially refractory to treat and often recurs. Objective measurement of melanin amount helps evaluate the treatment response of pigmentary disorders. However, naked-eye evaluation is subjective to weariness and bias. We used a cellular resolution full-field optical coherence tomography (FF-OCT) to assess melanin features of melasma lesions and perilesional skin on the cheeks of eight Asian patients. A computer-aided detection (CADe) system is proposed to mark and quantify melanin. This system combines spatial compounding-based denoising convolutional neural networks (SC-DnCNN), and through image processing techniques, various types of melanin features, including area, distribution, intensity, and shape, can be extracted. Through evaluations of the image differences between the lesion and perilesional skin, a distribution-based feature of confetti melanin without layering, two distribution-based features of confetti melanin in stratum spinosum, and a distribution-based feature of grain melanin at the dermal–epidermal junction, statistically significant findings were achieved (p-values = 0.0402, 0.0032, 0.0312, and 0.0426, respectively). FF-OCT enables the real-time observation of melanin features, and the CADe system with SC-DnCNN was a precise and objective tool with which to interpret the area, distribution, intensity, and shape of melanin on FF-OCT images. |
| نوع الوثيقة: |
text |
| وصف الملف: |
application/pdf |
| اللغة: |
English |
| Relation: |
Machine Learning and Artificial Intelligence in Diagnostics; https://dx.doi.org/10.3390/diagnostics11081498 |
| DOI: |
10.3390/diagnostics11081498 |
| الاتاحة: |
https://doi.org/10.3390/diagnostics11081498 |
| Rights: |
https://creativecommons.org/licenses/by/4.0/ |
| رقم الانضمام: |
edsbas.5091DFA8 |
| قاعدة البيانات: |
BASE |