Skin Lesion Segmentation
59 papers with code • 2 benchmarks • 1 datasets
Most implemented papers
Automatic skin lesion segmentation with fully convolutional-deconvolutional networks
This paper summarizes our method and validation results for the ISBI Challenge 2017 - Skin Lesion Analysis Towards Melanoma Detection - Part I: Lesion Segmentation
Dense Pooling layers in Fully Convolutional Network for Skin Lesion Segmentation
One of the essential tasks in medical image analysis is segmentation and accurate detection of borders.
Deeply Supervised Rotation Equivariant Network for Lesion Segmentation in Dermoscopy Images
Our best model achieves 77. 23\%(JA) on the test dataset, outperforming the state-of-the-art challenging methods and further demonstrating the effectiveness of our proposed deeply supervised rotation equivariant segmentation network.
Automatic Skin Lesion Segmentation Using Deep Fully Convolutional Networks
This paper summarizes our method and validation results for the ISIC Challenge 2018 - Skin Lesion Analysis Towards Melanoma Detection - Task 1: Lesion Segmentation
Automatic Skin Lesion Segmentation Using GrabCut in HSV Colour Space
Skin lesion segmentation is one of the first steps towards automatic Computer-Aided Diagnosis of skin cancer.
A Kernelized Manifold Mapping to Diminish the Effect of Adversarial Perturbations
The linear and non-flexible nature of deep convolutional models makes them vulnerable to carefully crafted adversarial perturbations.
Handling Inter-Annotator Agreement for Automated Skin Lesion Segmentation
We also evaluate how conditioning the ground truths using different (but very simple) algorithms may help to enhance agreement and may be appropriate for some use cases.
SLSNet: Skin lesion segmentation using a lightweight generative adversarial network
Thus, this article aims to achieve precise skin lesion segmentation with minimum resources: a lightweight, efficient generative adversarial network (GAN) model called SLSNet, which combines 1-D kernel factorized networks, position and channel attention, and multiscale aggregation mechanisms with a GAN model.
Impact of Adversarial Examples on Deep Learning Models for Biomedical Image Segmentation
Given that a large portion of medical imaging problems are effectively segmentation problems, we analyze the impact of adversarial examples on deep learning-based image segmentation models.
Skin Lesion Segmentation using SegNet with Binary Cross-Entropy
In this paper a simple and computationally efficient approach as per the complexity has been presented for Automatic Skin Lesion Segmentation using a Deep Learning architecture called SegNet including some additional specifications for the improvisation of the results.