Breast Cancer Detection in Infrared Thermal Images Using Convolutional Neural Networks: A Transfer Learning Approach-Reference-Cited by-同舟云学术

Breast Cancer Detection in Infrared Thermal Images Using Convolutional Neural Networks: A Transfer Learning Approach

Published:2021 Issue: Volume: Page:63-74
ISSN:2194-5357
Container-title:Advances in Intelligent Systems and Computing
language:
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Author:

Davies Swapna,Anand S

Publisher

Springer International Publishing

Link

https://link.springer.com/content/pdf/10.1007/978-3-030-73689-7_7

Reference15 articles.

1. Wahab, A.A., Salim, M.I.M., Aziz, M.N.C.: In vivo thermography-based image for early detection of breast cancer using two-tier segmentation algorithm and artificial neural network. In: Ng, E., Etehadtavakol, M. (eds.) Application of Infrared to Biomedical Sciences. Series in Bio-Engineering, vol. 1, pp. 109–131. Springer, Singapore (2017)

2. Ramesh O., Ali K., Sadaf A., Masoume N., Mansour A., Mitra N., Afsaneh A., Nasrin A., Khojasteh B., Shahrzad I.: Comparison of the accuracy of thermography and mammography in the detection of breast cancer. Breast Care Multi. J. Res. Diagn. Ther. Breast Dis. 11(4), 260-264 (2016)

3. Tan, T.Z., Quek, C., Ng, G.S., Ng, E.Y.K.: A novel cognitive interpretation of breast cancer thermography with complementary learning fuzzy neural memory structure. Expert Syst. Appl. 33(3), 652–666 (2007)

4. Ng, E.Y.K., Fok, S.C., Peh, Y.C., Ng, F.C., Sim, L.S.J.: Computerized detection of breast cancer with artificial intelligence and thermograms. J. Med. Eng. Technol. 26(4), 152–157 (2002)

5. Sahiner, B., et al.: Classification of mass and normal breast tissue: a convolution neural network classifier with spatial domain and texture images. IEEE Trans. Med. Imaging 15(5), 598–610 (1996)