Skin lesion classification using CNNs with grouping of multi-scale attention and class-specific loss weighting-Reference-Cited by-同舟云学术

Skin lesion classification using CNNs with grouping of multi-scale attention and class-specific loss weighting

Published:2022-11 Issue: Volume:226 Page:107166
ISSN:0169-2607
Container-title:Computer Methods and Programs in Biomedicine
language:en
Short-container-title:Computer Methods and Programs in Biomedicine

Author:

Qian Shenyi^ORCID,Ren Kunpeng,Zhang Weiwei,Ning Haohan

Publisher

Elsevier BV

Subject

Health Informatics,Computer Science Applications,Software

Reference45 articles.

1. Colorectal cancer statistics, 2017;Siegel;CA Cancer J. Clin.,2017

2. Early detection and treatment of skin cancer;Jerant;Am. Fam. Physician,2000

3. Final version of 2009 AJCC melanoma staging and classification;Balch;J. Clin. Oncol.,2009

4. Combinations of radiation therapy and immunotherapy for melanoma: a review of clinical outcomes;Barker;Int. J. Radiat. Oncol. Biol. Phys.,2014

5. Skin lesion analysis toward melanoma detection: a challenge at the 2017 international symposium on biomedical imaging (ISBI), hosted by the international skin imaging collaboration (ISIC);Codella,2018

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