ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detection

Abstract

Our system addresses Part 1, Lesion Segmentation and Part 3, Lesion Classification of the ISIC 2017 challenge. Both algorithms make use of deep convolutional networks to achieve the challenge objective.

arXiv commentISIC2017

References in corpus (1)

• Adam: A Method for Stochastic Optimization

Cited by in corpus (13)

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• Transformation Consistent Self-ensembling Model for Semi-supervised Medical Image Segmentation
• Segmentation of Skin Lesions and their Attributes Using Multi-Scale Convolutional Neural Networks and Domain Specific Augmentations
• A Smartphone based Application for Skin Cancer Classification Using Deep Learning with Clinical Images and Lesion Information
• Star Shape Prior in Fully Convolutional Networks for Skin Lesion Segmentation
• Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images
• Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images
• Deep neural network ensemble by data augmentation and bagging for skin lesion classification
• Improving Dermoscopic Image Segmentation with Enhanced Convolutional-Deconvolutional Networks
• Lesion Net -- Skin Lesion Segmentation Using Coordinate Convolution and Deep Residual Units
• Realistic Hair Simulation Using Image Blending
• PL-Net: Progressive Learning Network for Medical Image Segmentation
• The Effects of Image Pre- and Post-Processing, Wavelet Decomposition, and Local Binary Patterns on U-Nets for Skin Lesion Segmentation