Low Processing Power Algorithm to Segment Tumors in Mammograms
Author:
Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-030-70601-2_271
Reference11 articles.
1. Padhi S, Rup S, Saxena S, Mohanty F (2019) Mammogram segmentation methods: a brief review. In: 2nd International conference on intelligent communication and computational techniques (ICCT). Jaipur, India, pp 218–223
2. Lee RS et al (2017) A curated mammography data set for use in computer-aided detection and diagnosis research. Sci Data 4:170–177
3. Moreira IC, Ramos I, Ventura SR, Rodrigues PP (2019) Learner’s perception, knowledge and behavior assessment within a breast imaging e-learning course for radiographers. Eur J Radiol 111:47–55
4. Ekpo EU et al (2015) Breast composition: measurement and clinical use. Radiography 21(4):324–333
5. Gaur S et al (2013) Architectural distortion of the breast. Am J Roentgenol 201(5):W662–W670
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