Non-melanoma skin cancer segmentation for histopathology dataset-Reference-Cited by-同舟云学术

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Non-melanoma skin cancer segmentation for histopathology dataset

Published:2021-12 Issue: Volume:39 Page:107587
ISSN:2352-3409
Container-title:Data in Brief
language:en
Short-container-title:Data in Brief

Author:

Thomas Simon M.^ORCID,Lefevre James G.^ORCID,Baxter Glenn^ORCID,Hamilton Nicholas A.^ORCID

Publisher

Elsevier BV

Subject

Multidisciplinary

Reference5 articles.

1. Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer;Thomas;Med. Image Anal.,2021

2. Characterization of tissue types in basal cell carcinoma images via generative modelling and concept vectors;Thomas;Comput. Med. Imaging Graph.,2021

3. Epidemiology of melanoma and nonmelanoma skin cancer;Geller;Semin. Oncol. Nurs.,2003

4. Incidence estimate of nonmelanoma skin cancer (keratinocyte carcinomas) in the U.S. population, 2012;Rogers;JAMA Dermatol.,2015

5. Non-melanoma skin cancer in Australia: the 2002 national survey and trends since 1985;Staples;Med. J. Aust.,2006

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1. SPMLD: A skin pathological image dataset for non-melanoma with detailed lesion area annotation;Computers in Biology and Medicine;2024-09

2. Two-dimensional hybrid incremental learning (2DHIL) framework for semantic segmentation of skin tissues;Image and Vision Computing;2024-08

3. Two-dimensional hybrid incremental learning (2DHIL) framework for semantic segmentation of skin tissues;Image and Vision Computing;2024-08

4. Artificial intelligence for nonmelanoma skin cancer;Clinics in Dermatology;2024-06

5. Transformer-based framework for multi-class segmentation of skin cancer from histopathology images;Frontiers in Medicine;2024-04-29

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