Application of Image Segmentation and Convolutional Neural Network in Classification Algorithms for Mammary X-ray Molybdenum Target Image-Reference-Cited by-同舟云学术

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Application of Image Segmentation and Convolutional Neural Network in Classification Algorithms for Mammary X-ray Molybdenum Target Image

Published:2020 Issue: Volume: Page:175-187
ISSN:1876-1100
Container-title:Medical Imaging and Computer-Aided Diagnosis
language:
Short-container-title:

Author:

Zhang Minghuan,Liu Wenjian,Zhang Xuan,Chen Ying,Gu Yajia,Xiao Qin

Publisher

Springer Singapore

Link

http://link.springer.com/content/pdf/10.1007/978-981-15-5199-4_18

Reference32 articles.

1. Siegel, R.L., Miller, K.D., Jemal, A.: Cancer statistics. CA Cancer J. Clin. 68, 7–30 (2018)

2. Canadian Cancer Society’s Advisory Committee on Cancer Statistics: Canadian Cancer Statistics 2015. Toronto, Canadian Cancer Society (2015)

3. Khan, S., Khan, A., Maqsood, M., et al.: Optimized gabor feature extraction for mass classification using cuckoo search for big data e-healthcare. J Grid Comput 17, 239–254 (2019)

4. Breast Cancer Screening: International Agency for Research on Cancer (IARC) Handbooks of Cancer Prevention. WHO and IARC, Lyon (2016)

5. D’Orsi, C.J.: ACR BI-RADS Atlas: Breast imaging reporting and data system. American College of Radiology, Reston (2013)

Cited by 1 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. Segmentation of breast molybdenum target image lesions based on semi-supervised fuzzy clustering;Journal of Intelligent & Fuzzy Systems;2023-06-01

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