Journal
COMPUTER ANALYSIS OF IMAGES AND PATTERNS, CAIP 2019, PT I
Volume 11678, Issue -, Pages 89-101Publisher
SPRINGER INTERNATIONAL PUBLISHING AG
DOI: 10.1007/978-3-030-29888-3_8
Keywords
Deep learning; Convolutional Neural Networks; Transfer learning; Skin lesion segmentation
Funding
- European Union [825111]
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This paper presents a novel strategy to perform skin lesion segmentation from dermoscopic images. We design an effective segmentation pipeline, and explore several pre-training methods to initialize the features extractor, highlighting how different procedures lead the Convolutional Neural Network (CNN) to focus on different features. An encoder-decoder segmentation CNN is employed to take advantage of each pre-trained features extractor. Experimental results reveal how multiple initialization strategies can be exploited, by means of an ensemble method, to obtain state-of-the-art skin lesion segmentation accuracy.
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