Novel lymph node segmentation and proliferation index measurement for skin melanoma biopsy images-Reference-Cited by-同舟云学术

Novel lymph node segmentation and proliferation index measurement for skin melanoma biopsy images

Published:2019-04 Issue: Volume:73 Page:19-29
ISSN:0895-6111
Container-title:Computerized Medical Imaging and Graphics
language:en
Short-container-title:Computerized Medical Imaging and Graphics

Author:

Alheejawi Salah,Xu Hongming^ORCID,Berendt Richard^ORCID,Jha Naresh,Mandal Mrinal

Funder

Natural Sciences and Engineering Research Council of CanadaNatural Sciences and Engineering Research Council of Canada (NSERC)

Ministry of Higher Education and Scientific Research (MOHESR)

Publisher

Elsevier BV

Subject

Computer Graphics and Computer-Aided Design,Health Informatics,Computer Vision and Pattern Recognition,Radiology Nuclear Medicine and imaging,Radiological and Ultrasound Technology

Reference23 articles.

1. Histological stains: a literature review and case study;Alturkistani;Glob. J. Health Sci.,2016

2. Cancer Facts and Figures;American Cancer Society,2018

3. Melanoma of the skin;Balch,2010

4. Comparative methodological analysis of erbB-2/HER-2 gene dosage, chromosomal copy number and protein overexpression in breast carcinoma tissues for diagnostic use;Bánkfalvi;Histopathology,2000

5. Support vector clustering;Ben-Hur;J. Mach. Learn. Res.,2001

Cited by 23 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. Computational methods for metastasis detection in lymph nodes and characterization of the metastasis-free lymph node microarchitecture: A systematic-narrative hybrid review;Journal of Pathology Informatics;2024-12

2. The Depth Estimation and Visualization of Dermatological Lesions: A Novel Methodology (Preprint);2024-04-23

3. Survey on computer-aided automated melanoma detection;Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization;2024-01-19

4. A Review of Recent Advances in Computer-Aided Detection Methods Using Hyperspectral Imaging Engineering to Detect Skin Cancer;Cancers;2023-11-29

5. Artificial Intelligence based real-time automatic detection and classification of skin lesion in dermoscopic samples using DenseNet-169 architecture;Journal of Intelligent & Fuzzy Systems;2023-10-04