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Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks

07/17/2018

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by Hongming Xu, et al.

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This paper summarizes our method and validation results for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection - Task 1: Lesion Segmentation

Hongming Xu
5 publications
Tae Hyun Hwang
3 publications

research

∙ 03/15/2017

Automatic skin lesion segmentation with fully convolutional-deconvolutional networks

This paper summarizes our method and validation results for the ISBI Cha...

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∙ 03/01/2017

ISIC 2017 - Skin Lesion Analysis Towards Melanoma Detection

Our system addresses Part 1, Lesion Segmentation and Part 3, Lesion Clas...

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∙ 03/02/2017

Skin Lesion Analysis Towards Melanoma Detection Using Deep Learning Network

Skin lesion is a severe disease in world-wide extent. Early detection of...

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∙ 07/24/2018

ISIC 2017 Skin Lesion Segmentation Using Deep Encoder-Decoder Network

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∙ 12/29/2017

Dense Fully Convolutional Network for Skin Lesion Segmentation

Skin cancer is a deadly disease and is on the rise in the world. Compute...

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∙ 03/09/2017

LesionSeg: Semantic segmentation of skin lesions using Deep Convolutional Neural Network

We present a method for skin lesion segmentation for the ISIC 2017 Skin ...

0 Dhanesh Ramachandram, et al. ∙

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∙ 03/03/2017

A Novel Multi-task Deep Learning Model for Skin Lesion Segmentation and Classification

In this study, a multi-task deep neural network is proposed for skin les...

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