This document contains 8 references related to breast cancer detection and self-examination. The references include master's theses from De La Salle University published between 2014-2015 that developed computer vision algorithms and systems to help with breast self-examination. Additional references include reports from the World Health Organization, International Agency for Research on Cancer, and International Telecommunications Union providing statistics on breast cancer incidence and mortality in the Asia-Pacific region.

4. (Youlden, 2014)

43. Eman, M. (2014). Design and development of Computer Vision Algorithm for a Real-time Breast Self-Examination. DLSU Master’
s thesis 2014.
Heo, J., Chun, M., Lee, K. Y., Oh, Y. T., Noh, O. K., & Park, R. W. (2013). Effects of a smartphone application on breast self-
examination: a feasibility study. Healthcare informatics research, 19(4), 250-260.
Jose, A. (2015). Development of Depth Level Estimation Algorithm for Breast Self-Examination. DLSU Master’s thesis 2015.
International Agency for Research on Cancer (IARC/WHO) (2012). THE GLOBOCAN PROJECT, (http://globocan.iarc.fr,
accessed 1 January 2016)
International Telecommunications Union (2015). The world in 2015: ICT facts and figures. Geneva.
(http://www.itu.int/en/ITU-D/Statistics/Documents/facts/ICTFactsFigures2015.pdf , accessed 1 January 2016)
Masilang, R. (2014). Design and development of a Computer-vision-based Breast Self-Examination Instruction and Supervision
System. DLSU Master’s thesis 2014.
World Health Organization (http://www.who.int/cancer/detection/breastcancer/en/, accessed March 4, 2016)
Youlden, D. R., Cramb, S. M., Yip, C. H., & Baade, P. D. (2014). Incidence and mortality of female breast cancer in the Asia-
Pacific region. Cancer biology & medicine, 11(2), 101-115.