ISIC 2017 Skin Lesion Segmentation Using Deep Encoder-Decoder Network

07/24/2018
by   Ngoc-Quang Nguyen, et al.
0

This paper summarizes our method and validation results for part 1 of the ISBI Challenge 2018. Our algorithm makes use of deep encoder-decoder network and novel skin lesion data augmentation to segment the challenge objective. Besides, we also propose an effective testing strategy by applying multi-model comparison.

READ FULL TEXT
research
07/17/2018

Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks

This paper summarizes our method and validation results for the ISIC Cha...
research
05/25/2018

SLSDeep: Skin Lesion Segmentation Based on Dilated Residual and Pyramid Pooling Networks

Skin lesion segmentation (SLS) in dermoscopic images is a crucial task f...
research
01/26/2019

Deep Convolutional Encoder-Decoders with Aggregated Multi-Resolution Skip Connections for Skin Lesion Segmentation

The prevalence of skin melanoma is rapidly increasing as well as the rec...
research
05/02/2023

Oil Spill Segmentation using Deep Encoder-Decoder models

Crude oil is an integral component of the modern world economy. With the...
research
02/21/2022

Deep Residual Inception Encoder-Decoder Network for Amyloid PET Harmonization

Introduction Multiple positron emission tomography (PET) tracers are av...
research
11/25/2020

A Odor Labeling Convolutional Encoder-Decoder for Odor Sensing in Machine Olfaction

Nowadays, machine olfaction has been widely used in many fields. In this...
research
09/18/2021

Small Lesion Segmentation in Brain MRIs with Subpixel Embedding

We present a method to segment MRI scans of the human brain into ischemi...

Please sign up or login with your details

Forgot password? Click here to reset