Results 1 to 10 of about 313,991 (115)

Advanced hybrid transformer CNN framework for improved skin lesion classification and segmentation [PDF]

open access: yesScientific Reports
As reported by the World Health Organization (WHO), Skin Cancer (SC) is a growing medical concern with millions of cases diagnosed each year. Deep Learning methods show promising results in early detection and classification of SC, but still face ...
Nazish Yousaf   +4 more
doaj   +2 more sources

LTPNet: Lesion-Aware Triple-Path Feature Fusion Network for Skin Lesion Segmentation [PDF]

open access: yesJournal of Imaging
Skin lesion segmentation has achieved notable progress in recent years; however, accurate delineation remains challenging due to complex backgrounds, ambiguous boundaries, and low lesion-to-skin contrast.
Yange Sun   +5 more
doaj   +2 more sources

Lightweight Unet with depthwise separable convolution for skin lesion segmentation [PDF]

open access: yesScientific Reports
Accurate segmentation of skin lesions is crucial for the early diagnosis of skin diseases, as clear lesion boundaries facilitate the comprehensive extraction of lesion features.
Yong Li, Bosheng Hu, Xia Wang, Kun Liu
doaj   +2 more sources

Skin Lesion Segmentation in Dermoscopic Images with Combination of YOLO and GrabCut Algorithm

open access: yesDiagnostics, 2019
Skin lesion segmentation has a critical role in the early and accurate diagnosis of skin cancer by computerized systems. However, automatic segmentation of skin lesions in dermoscopic images is a challenging task owing to difficulties including artifacts
Halil Murat Ünver, Enes Ayan
doaj   +3 more sources

Skin lesion segmentation method for dermoscopic images with convolutional neural networks and semantic segmentation [PDF]

open access: yesКомпьютерная оптика, 2021
Melanoma skin cancer is one of the most dangerous forms of skin cancer because it grows fast and causes most of the skin cancer deaths. Hence, early detection is a very important task to treat melanoma.
Dang N.H. Thanh   +4 more
doaj   +1 more source

A Probabilistic-Based Deep Learning Model for Skin Lesion Segmentation

open access: yesApplied Sciences, 2021
The analysis and detection of skin cancer diseases from skin lesion have always been tedious when done manually. The complex nature of skin lesion images is one of the key reasons for this. The skin lesion images contain noise and artifacts such as hairs,
Adekanmi Adeyinka Adegun   +2 more
doaj   +1 more source

Skin Lesion Classification and Detection Using Machine Learning Techniques: A Systematic Review

open access: yesDiagnostics, 2023
Skin lesions are essential for the early detection and management of a number of dermatological disorders. Learning-based methods for skin lesion analysis have drawn much attention lately because of improvements in computer vision and machine learning ...
Taye Girma Debelee
doaj   +1 more source

Dermoscopy Image Classification Based on StyleGAN and DenseNet201

open access: yesIEEE Access, 2021
Melanoma is considered one of the most lethal skin cancers. However, skin lesion classification based on deep learning diagnostic techniques is a challenging task owing to the insufficiency of labeled skin lesion images and intraclass-imbalanced datasets.
Chen Zhao   +5 more
doaj   +1 more source

A machine learning approach to automatic detection of irregularity in skin lesion border using dermoscopic images [PDF]

open access: yesPeerJ Computer Science, 2020
Skin lesion border irregularity is considered an important clinical feature for the early diagnosis of melanoma, representing the B feature in the ABCD rule.
Abder-Rahman Ali   +3 more
doaj   +2 more sources

Dermatological Manifestations in COVID-19 Disease

open access: yesSakarya Tıp Dergisi, 2021
Although the etio-pathogenesis of skin lesions in COVID-19 is yet not clear, several theories have been proposed. One of them is cytokine storm causing thrombophilic arteritis in COVID-19 patients due to activation of endothelial cells and macrophages ...
Öner Özdemir   +2 more
doaj   +1 more source

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