☆ 4.1 Article Data Paper

Non-melanoma skin cancer segmentation for histopathology dataset

DATA IN BRIEF (2021)

Characterization of tissue types in basal cell carcinoma images via generative modeling and concept vectors

S. M. Thomas et al.

Summary: The promise of machine learning methods as decision support systems for pathologists continues to grow, with interpretable implementations being essential for successful adoption. By applying generative methods to histological images of basal cell carcinoma, rich latent vectors corresponding to various tissue morphologies were extracted.

COMPUTERIZED MEDICAL IMAGING AND GRAPHICS (2021)

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Article Computer Science, Artificial Intelligence

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer

Simon M. Thomas et al.

Summary: This study applies interpretable deep learning methods to analyze the most common skin cancers in a histological setting, demonstrating the potential for automatic machine analysis of dermatopathology work. By characterizing tissue into meaningful dermatological classes, the research aims to pave the way for future computer aided diagnosis systems with human interpretable outcomes.

MEDICAL IMAGE ANALYSIS (2021)

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Article Dermatology

Incidence Estimate of Nonmelanoma Skin Cancer (Keratinocyte Carcinomas) in the US Population, 2012

Howard W. Rogers et al.

JAMA DERMATOLOGY (2015)

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Article Medicine, General & Internal

Non-melanoma skin cancer in Australia: the 2002 national survey and trends since 1985

MP Staples et al.

MEDICAL JOURNAL OF AUSTRALIA (2006)

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Non-melanoma skin cancer segmentation for histopathology dataset

相关参考文献

Characterization of tissue types in basal cell carcinoma images via generative modeling and concept vectors

Interpretable deep learning systems for multi-class segmentation and classification of non-melanoma skin cancer

Incidence Estimate of Nonmelanoma Skin Cancer (Keratinocyte Carcinomas) in the US Population, 2012

Non-melanoma skin cancer in Australia: the 2002 national survey and trends since 1985

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