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20092023
most citedA Survey on Deep Learning for Skin Lesion Segmentation

192 citations · 729 across the 35 of their papers we have counts for

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12 papers · 1 filter

eess.IV2023★ 1 cited

DermSynth3D: Synthesis of in-the-wild Annotated Dermatology Images

Ashish Sinha, Jeremy Kawahara, Arezou Pakzad +6

In recent years, deep learning (DL) has shown great potential in the field of dermatological image analysis. However, existing datasets in this domain have significant limitations,…

eess.IV2022★ 192 cited

A Survey on Deep Learning for Skin Lesion Segmentation

Zahra Mirikharaji, Kumar Abhishek, Alceu Bissoto +5

Skin cancer is a major public health problem that could benefit from computer-aided diagnosis to reduce the burden of this common disease. Skin lesion segmentation from images is a…

eess.IV2020

D-LEMA: Deep Learning Ensembles from Multiple Annotations -- Application to Skin Lesion Segmentation

Zahra Mirikharaji, Kumar Abhishek, Saeed Izadi +1

Medical image segmentation annotations suffer from inter- and intra-observer variations even among experts due to intrinsic differences in human annotators and ambiguous boundaries…

eess.IV2020

Matthews Correlation Coefficient Loss for Deep Convolutional Networks: Application to Skin Lesion Segmentation

Kumar Abhishek, Ghassan Hamarneh

The segmentation of skin lesions is a crucial task in clinical decision support systems for the computer aided diagnosis of skin lesions. Although deep learning-based approaches ha…

eess.IV2020

Patch-based Non-Local Bayesian Networks for Blind Confocal Microscopy Denoising

Saeed Izadi, Ghassan Hamarneh

Confocal microscopy is essential for histopathologic cell visualization and quantification. Despite its significant role in biology, fluorescence confocal microscopy suffers from t…

eess.IV2020★ 13 cited

Deep Learning for Biomedical Image Reconstruction: A Survey

Hanene Ben Yedder, Ben Cardoen, Ghassan Hamarneh

Medical imaging is an invaluable resource in medicine as it enables to peer inside the human body and provides scientists and physicians with a wealth of information indispensable…