Skin Lesion Segmentation
60 papers with code • 2 benchmarks • 1 datasets
University of Waterloo skin cancer database
Most implemented papers
Complementary Network with Adaptive Receptive Fields for Melanoma Segmentation
To tackle these issues, we propose a novel complementary network with adaptive receptive filed learning.
Illumination-based Transformations Improve Skin Lesion Segmentation in Dermoscopic Images
kakumarabhishek/Illumination-based-Transformations-Skin-Lesion-Segmentation
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The semantic segmentation of skin lesions is an important and common initial task in the computer aided diagnosis of dermoscopic images.
A generic ensemble based deep convolutional neural network for semi-supervised medical image segmentation
ruizhe-l/semi-segmentation
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To address this problem, we propose a generic semi-supervised learning framework for image segmentation based on a deep convolutional neural network (DCNN).
DRU-net: An Efficient Deep Convolutional Neural Network for Medical Image Segmentation
MinaJf/DRU-net
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In comparison with ResNet-based, DenseNet-based and attention network (AttnNet) based methods within the same encoder-decoder network structure, our method achieves significantly higher segmentation accuracy with fewer number of model parameters than DenseNet and AttnNet.
Less is More: Sample Selection and Label Conditioning Improve Skin Lesion Segmentation
vribeiro1/skin-lesion-segmentation-agreement
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Segmenting skin lesions images is relevant both for itself and for assisting in lesion classification, but suffers from the challenge in obtaining annotated data.
The Effects of Skin Lesion Segmentation on the Performance of Dermatoscopic Image Classification
In this study, we explicitly investigated the impact of using skin lesion segmentation masks on the performance of dermatoscopic image classification.
Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation
The segmentation of skin lesions is a crucial task in clinical decision support systems for the computer aided diagnosis of skin lesions.
MSRF-Net: A Multi-Scale Residual Fusion Network for Biomedical Image Segmentation
The proposed MSRF-Net allows to capture object variabilities and provides improved results on different biomedical datasets.
Boundary-aware Transformers for Skin Lesion Segmentation
Skin lesion segmentation from dermoscopy images is of great importance for improving the quantitative analysis of skin cancer.
MT-TransUNet: Mediating Multi-Task Tokens in Transformers for Skin Lesion Segmentation and Classification
However, these approaches formulated skin cancer diagnosis as a simple classification task, dismissing the potential benefit from lesion segmentation.
