참고문헌 (24)

1. 1 Arora N Martins D Ruggerio D Tousimis E Swistel AJ Osborne MP Effectiveness of a noninvasive digital infrared thermal imaging system in the detection of breast cancer Am J Surg 2008 196 523–6 18809055 

2. 2 Boquete L Ortega S Miguel-Jiménez JM Rodríguez-Ascariz JM Blanco R Automated detection of breast cancer in thermal infrared images, based on independent component analysis J Med Syst 2012 36 103–11 20703744 

3. 3 Chavez KJ Garimella SV Lipkowitz S Triple negative breast cancer cell lines: one tool in the search for better treatment of triple negative breast cancer Breast Dis 2010 32 35–48 21778573 

4. 4 Cuevas E Zaldivar D Pérez M Procesamiento digital de imágenes con MATLAB y Simulink 2010 Mexico Alfaomega 472 474 

5. 5 Dayakshini D Kamath S Prasad K Rajagopal KV Segmentation of breast thermogram images for the detection of breast cancer – a projection profile approach JOIG 2015 3 47–51 

6. 6 Francis SV Sasikala M Bhavani Bharathi G Jaipurkar SD Breast cancer detection in rotational thermography images using texture features Infrared Phys Techn 2014 67 490–6 

7. 7 Gautherie M Thermopathology of breast cancer: measurement and analysis of in vivo temperature and blood flow Ann N Y Acad Sci 1980 335 383–415 6931533 

8. 8 Ghayoumi Zadeh H Haddadnia J Montazeri A A model for diagnosing breast cancerous tissue from thermal images using active contour and lyapunov exponent Iran J Public Health 2016 45 657–69 27398339 

9. 9 Ghayoumi Zadeh H Haddadnia J Rahmani Seryasat O Mostafavi Isfahani SM Segmenting breast cancerous regions in thermal images using fuzzy active contours EXCLI J 2016 15 532–50 28096784 

10. 10 González FJ Non-invasive estimation of the metabolic heat production of breast tumors using digital infrared imaging Quant Infr Therm J 2011 8 139–48 

11. 11 Guzman-Cabrera R Guzman-Sepulveda JR Parada AG Garcia JR Cisneros MT Baleanu D Digital processing of thermographic images for medical applications Rev Chim 2016 67 53 56 

    상세보기

12. 12 Han F Shi G Liang C Wang L Li K A simple and efficient method for breast cancer diagnosis based on infrared thermal imaging Cell Biochem Biophys 2015 71 491–8 25194831 

13. 13 INEGI. Instituto Nacional de Estadística y Geografía 2015 9 September 2018 Available from: http://www.inegi.org.mx/saladeprensa/aproposito/2015/mama0.pdf 

14. 14 Jones BF A reappraisal of the use of infrared thermal image analysis in medicine IEEE Trans Med Imaging 1998 17 1019–27 10048859 

15. 15 Keyserlingk JR Ahlgren PD Yu E Belliveau N Infrared imaging of the breast: initial reappraisal using high-resolution digital technology in 100 successive cases of stage I and II breast cancer Breast J 1998 4 245–51 21223443 

16. 16 Krawczyk B Schaefer G A hybrid classifier committee for analysing asymmetry features in breast thermograms Appl Soft Comput 2014 20 112–8 

17. 17 Milosevic M Jankovic D Peulic A Thermography based breast cancer detection using texture features and minimum variance quantization EXCLI J 2014 13 1204–15 26417334 

18. 18 Rastghalam R Pourghassem H Breast cancer detection using MRF-based probable texture feature and decision-level fusion-based classification using HMM on thermography images Pattern Recognit 2016 51 176 186 

    상세보기

19. 19 Schaefer G ACO classification of thermogram symmetry features for breast cancer diagnosis Memetic Comp 2014 6 207–12 

20. 20 Wang J Chang K-J Chen C-Y Chien K-L Tsai Y-S Wu Y-M Evaluation of the diagnostic performance of infrared imaging of the breast: a preliminary study Biomed Eng Online 2010 9 3 20055999 

    상세보기

21. 21 WHO Breast cancer: prevention and control 2018 8 September 2018 Available from: http://www.who.int/cancer/detection/breastcancer/en/ 

22. 22 Wishart GC Campisi M Boswell M Chapman D Shackleton V Iddles S The accuracy of digital infrared imaging for breast cancer detection in women undergoing breast biopsy Eur J Surg Oncol 2010 36 535–40 20452740 

23. 23 Yao X Wei W Li J Wang L Xu Z Wan Y A comparison of mammography, ultrasonography, and far-infrared thermograhy with pathological results in screening and early diagnosis of breast cancer Asian Biomed 2014 8 11–9 

24. 24 Zhang X Li X Feng Y A medical image segmentation algorithm based on bi-directional region growing Optik 2015 126 2398–404