Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM)

机译：支持向量机（SVM）基于深度学习的黑素瘤皮肤病变分割和分类

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摘要

The main objective of this study is to improve the classification performance of melanoma using deep learning based automatic skin lesion segmentation. It can be assist medical experts on early diagnosis of melanoma on dermoscopy images.

机译：这项研究的主要目的是使用基于深度学习的自动皮肤病变分割来提高黑色素瘤的分类性能。它可以帮助医学专家在皮肤镜图像上早期诊断黑色素瘤。

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期刊名称 Asian Pacific Journal of Cancer Prevention : APJCP
作者
Seeja R D; Suresh A;
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作者单位

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年(卷),期 2019(20),5
年度 2019
页码 -1
总页数 7
原文格式 PDF
正文语种
中图分类肿瘤学;
关键词
Melanoma; deep learning; dermoscopy; segmentation; classification;

机译：黑色素瘤;深度学习;皮肤镜检查;分割;分类;

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专利

1. Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM) [J] . Seeja R D, Suresh A Asian Pacific Journal of Cancer Prevention . 2019,第5期

机译：支持向量机（SVM）基于深度学习的黑素瘤皮肤病变分割和分类
2. Active Contour Based Segmentation and Classification for Pleura Diseases Based on Otsu’s Thresholding and Support Vector Machine (SVM) [J] . M Malathi, P Sinthia, K Jalaldeen Asian Pacific Journal of Cancer Prevention . 2019,第1期

机译：基于大津市阈值和支持向量机（SVM）的主动轮廓基于胸膜疾病的分割和分类
3. Robust classification approach for segmentation of blood defects in cod fillets based on deep convolutional neural networks and support vector machines and calculation of gripper vectors for robotic processing [J] . Computers and Electronics in Agriculture . 2017,第期

机译：基于深卷积神经网络的COD圆角分割血液缺陷分割的鲁棒分类方法及夹钳矢量夹具矢量计算
4. Classification of Malignant Melanoma and Benign Nevi from Skin Lesions Based on Support Vector Machine [C] . Mahmoud Mohamed Khalad Abu, Al-Jumaily Adel, Maali Yashar, International Conference on Computational Intelligence, Modelling and Simulation . 2013

机译：基于支持向量机的皮肤病变恶性黑色素瘤和良性痣分类
5. Efficacy Testing of Food Industry Cleaning Agents on the Removal of Engineered Nanoparticles from the Skins of Grape Tomatoes (Solanum lycopersicum) Using Attenuated Total Reflection Fourier Transform Infrared Spectroscopy (ATR FTIR) and Support Vector Machine (SVM) Learning [D] . Wood, Elizabeth Alene 2018

机译：使用衰减全反射傅立叶变换红外光谱（ATR FTIR）和支持向量机（SVM）学习对食品工业清洁剂去除葡萄西红柿（Solanum lycopersicum）皮肤中工程纳米颗粒的功效测试
6. Active Contour Based Segmentation and Classification for Pleura Diseases Based on Otsu’s Thresholding and Support Vector Machine (SVM) [O] . M Malathi, P Sinthia, K Jalaldeen 2019

机译：基于大津市阈值和支持向量机（SVM）的主动轮廓基于胸膜疾病的分割和分类
7. Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM) [O] . Seeja R D, Suresh A 2019

机译：基于深度学习的皮肤病病变分割和使用支持向量机（SVM）的黑色素瘤分类

Deep Learning Based Skin Lesion Segmentation and Classification of Melanoma Using Support Vector Machine (SVM)

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