Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis-Reference-Cited by-同舟云学术

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Deep Learning Techniques for Breast Cancer Detection Using Medical Image Analysis

Published:2017-08-18 Issue: Volume: Page:159-186
ISSN:2212-9391
Container-title:Biologically Rationalized Computing Techniques For Image Processing Applications
language:
Short-container-title:

Author:

Selvathi D.,Aarthy Poornila A.

Publisher

Springer International Publishing

Link

http://link.springer.com/content/pdf/10.1007/978-3-319-61316-1_8

Reference20 articles.

1. Islam MS, Kaabouch N, Hu WC (2013) A survey of medical imaging techniques used for breast cancer detection. In: IEEE conference on Electro-Information Technology (EIT). IEEE Press, Rapid City, South Dakota, pp 1–5

2. Prasad SN, Houserkova D (2007) The role of various modalities in breast imaging. Biomed Pap Med Fac Univ Palacky Olomouc Czech Repub 151(2):209–218

3. Shyamala K, Girish HC, Murgod S (2014) Risk of tumor cell seeding through biopsy and aspiration cytology. J Int Soc Prev Commun Dent 4(1):5–11

4. Nagi J, Abdul Kareem S, Nagi F, Khaleel Ahmed S (2010) Automated breast profile segmentation for roi detection using digital mammograms. In: IEEE EMBS conference on biomedical engineering & sciences. IEEE Press, Kuala Lumpur, Malaysia, pp 87–92

5. Tan M, Zheng B, Leader JK, Gur D (2016) Association between changes in mammographic image features and risk for near-term breast cancer development. IEEE Trans Med Imaging 35(7):1719–1728

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