Detection of Malignant Melanomas in Dermoscopic Images Using Convolutional Neural Network with Transfer Learning

被引：6
|
作者：
Georgakopoulos, S., V [1 ]
Kottari, K. [1 ]
Delibasis, K. [1 ]
Plagianakos, V. P. [1 ,2 ]
Maglogiannis, I [2 ]
机构：
[1] Univ Thessaly, Dept Comp Sci & Biomed Informat, Papassiopoulou 2-4, Lamia, Greece
[2] Univ Piraeus, Dept Digital Syst, Piraeus, Greece
来源：
ENGINEERING APPLICATIONS OF NEURAL NETWORKS, EANN 2017 | 2017年 / 744卷
关键词：
Skin lesion; Melanoma detection; Computer Vision-based diagnostic systems; Convolutional neural networks - CNN; CNN architectures; Transfer learning; SKIN-CANCER; DIAGNOSIS; STREAKS;
D O I：
10.1007/978-3-319-65172-9_34
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
In this work, we report the use of convolutional neural networks for the detection of malignant melanomas against nevus skin lesions in a dataset of dermoscopic images of the same magnification. The technique of transfer learning is utilized to compensate for the limited size of the available image dataset. Results show that including transfer learning in training CNN architectures improves significantly the achieved classification results.
引用
收藏
页码：404 / 414
页数：11
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