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Automatic skin lesion segmentation

2017 Electric Electronics, Computer Science, Biomedical Engineerings' Meeting (EBBT), 2017
In the modern world, cancer has increasingly become a health problem. It has been listed as the first three disease among the ‘cause-known deaths’ in our country. Malignant Melanoma, one of the skin cancer types, is the cause of 75% of all skin cancer related deaths even though it is 4% of all skin cancer cases.
Haydar Ozkan   +3 more
openaire   +1 more source

Generative adversarial networks to segment skin lesions

2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), 2018
The accuracy of skin lesion segmentation has increased in recent years, thanks to advances in machine learning techniques and a large influx of dermoscopy images. However, there is still room for improvement as there exist many considerable challenges mainly due to the large variability in the appearance of lesions (i.e., shape, size, texture, and ...
Saeed Izadi   +3 more
openaire   +2 more sources

A Skin Lesion Semi-supervised Segmentation Method

2020 International Conference on Systems, Signals and Image Processing (IWSSIP), 2020
The skin is an essential system for the human body, also the most susceptible to diseases. The diagnosis of these diseases is made mainly through dermatoscopy images, a noninvasive procedure. This paper presents a semi-automatic method that can assist the physician in monitoring the skin lesion's evolution.
Elineide Silva Dos Santos   +5 more
openaire   +1 more source

The NL-SC Net for Skin Lesion Segmentation

2021
The problem of skin lesion segmentation remains to be a challenging task due to the low contrast of lesions, occlusions and varied sizes of foreground. The existing methods are unable to perform well on complex scenarios. In this paper, an accurate skin lesion segmentation method with Res-SC block and Res-NL block is proposed, which successfully ...
Ziming Chen, Shengsheng Wang 0001
openaire   +2 more sources

Macroscopic Skin Lesion Segmentation Using GrabCut

2020
Melanoma is one of the most dangerous forms of skin cancer with an apace increase in death rates each year. One major problem in Artificial Intelligence and Machine Learning is the issue of racial disparities. This leads to myriad problems in association with medical image analysis as the data fed to these algorithms are biased.
Verosha Pillay   +3 more
openaire   +1 more source

Skin Lesion Segmentation via Deep RefineNet

2017
Dermoscopy imaging has been a routine examination approach for skin lesion diagnosis. Accurate segmentation is the first step for automatic dermoscopy image assessment. The main challenges for skin lesion segmentation are numerous variations in viewpoint and scale of skin lesion region.
Xinzi He   +3 more
openaire   +1 more source

Dense Deconvolutional Network for Skin Lesion Segmentation

IEEE Journal of Biomedical and Health Informatics, 2019
Automatic delineation of skin lesion contours from dermoscopy images is a basic step in the process of diagnosis and treatment of skin lesions. However, it is a challenging task due to the high variation of appearances and sizes of skin lesions. In order to deal with such challenges, we propose a new dense deconvolutional network (DDN) for skin lesion ...
Hang Li   +7 more
openaire   +3 more sources

Efficient skin lesion segmentation with boundary distillation

Medical & Biological Engineering & Computing
Medical image segmentation models are commonly known for their complex structures, which often render them impractical for use on edge computing devices and compromising efficiency in the segmentation process. In light of this, the industry has proposed the adoption of knowledge distillation techniques.
Zaifang Zhang, Boyang Lu
openaire   +2 more sources

Ensemble Transductive Learning for Skin Lesion Segmentation

2019
Automated segmentation of skin lesions from dermoscopy images is helpful for the diagnosis and treatment of skin cancers. However, due to small annotated training set and the large visual difference in skins and lesions between subjects, the generalization performance of segmentation models are often limited.
Zhiying Cui   +3 more
openaire   +1 more source

Color Segmentation for Skin Lesions Classification

2008 Cairo International Biomedical Engineering Conference, 2008
Differential diagnosis of Erythemato-Squamos diseases is considered a real problem in dermatology. They all share the clinical features of erythematic and scaling, with very little differences. This paper introduces an unsupervised color segmentation procedure applied to one disease of this group named Atopic Dermatitis.
N. A. Masood   +2 more
openaire   +1 more source

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