Breast Cancer Segmentation and Detection Using U-net With Ultrasound Dataset

Author:

Rahman Md. Mijnaur1ORCID,Hossain Anwar2ORCID,Chakraborty Nipu2ORCID,Khan Md Rezaul Karim3ORCID

Affiliation:

1. Computer Science and Engineering , Southeast University, Bangladesh

2. Southeast University, Bangladesh

3. Maharishi International University, United States of America

Publisher

ACM

Reference21 articles.

1. R.L. Siegel K.D. Miller and A. Jemal. 2019. Cancer statistics 2019. CA: a cancer journal for clinicians 69 1 (2019) 7–34. DOI:https://doi.org/10.3322/caac.21551

2. Connected-UNets: a deep learning architecture for breast mass segmentation

3. M. Drozdzal E. Vorontsov G. Chartrand S. Kadoury and C. Pal. 2016. The Importance of Skip Connections in Biomedical Image Segmentation. In Deep Learning and Data Labeling for Medical Applications (Carneiro G. eds.) DLMIA LABELS 2016 Lecture Notes in Computer Science vol 10008. Springer Cham 234–241. DOI:https://doi.org/10.1007/978-3-319-46976-8_19

4. K. O'Shea and R. Nash. 2015. An Introduction to Convolutional Neural Networks. arXiv preprint arXiv:1511.08458.

5. O. Ronneberger, P. Fischer, and T. Brox. 2015. U-net: Convolutional networks for biomedical image segmentation. In Medical Image Computing and Computer-Assisted Intervention–MICCAI 2015: 18th International Conference, Munich, Germany, October 5-9, 2015, Proceedings, Part III 18, 234–241. Springer International Publishing.

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