Early melanoma diagnosis with mobile imaging

2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBC 2014

Volumn , Issue , 2014, Pages 6752-6757

  Do, Thanh Toan ^a   Zhou, Yiren ^a   Zheng, Haitian ^a   Cheung, Ngai Man ^a   Koh, Dawn ^a  

^a SINGAPORE UNIVERSITY OF TECHNOLOGY AND DESIGN   (Singapore)

Author keywords

[No Author keywords available]

Indexed keywords

DERMATOLOGY; DIAGNOSIS; ONCOLOGY; SMARTPHONES;

CONTROLLED CONDITIONS; DETECTION SYSTEM; LIGHTWEIGHT SYSTEMS; MELANOMA DETECTION; MEMORY CONSTRAINTS; SEGMENTATION RESULTS; SELECTION CRITERIA; SKIN LESION IMAGES;

MHEALTH;

ALGORITHM; COMPUTER ASSISTED DIAGNOSIS; DIAGNOSTIC IMAGING; EARLY DIAGNOSIS; HUMAN; MELANOMA; MOBILE PHONE; PATHOLOGY; PHOTOGRAPHY; SKIN; SKIN NEOPLASMS; SKIN PIGMENTATION;

ALGORITHMS; CELL PHONES; DIAGNOSTIC IMAGING; EARLY DETECTION OF CANCER; HUMANS; IMAGE INTERPRETATION, COMPUTER-ASSISTED; MELANOMA; PHOTOGRAPHY; SKIN; SKIN NEOPLASMS; SKIN PIGMENTATION;

EID: 84929484194     PISSN: None     EISSN: None     Source Type: Conference Proceeding    
DOI: 10.1109/EMBC.2014.6945178     Document Type: Conference Paper

References (25)

1. Roberto Battiti. Using mutual information for selecting features in supervised neural net learning. IEEE Transactions on Neural Networks, 5:537-550, 1994.
2. M. Emre Celebi, Hassan A. Kingravi, Bakhtiyar Uddin, Hitoshi Iyatomi, Y. Alp Aslandogan, William V. Stoecker, and Randy H. Moss. A methodological approach to the classification of dermoscopy images. Comp. Med. Imag. and Graph., 31(6):362-373, 2007.
3. Chih-Chung Chang and Chih-Jen Lin. Libsvm: A library for support vector machines. ACM TIST, 2(3):27, 2011.
4. Doukas Charalampos, Stagkopoulos Paris, Kiranoudis Chris T, and Maglogiannis Ilias. Automated skin lesion assessment using mobile technologies and cloud platforms. in Conf Proc IEEE Eng Med Biol Soc, pages 2444-24447, 2012.
5. Taeg Sang Cho, William T Freeman, and Hensin Tsao. A reliable skin mole localization scheme. in Computer Vision, 2007. ICCV 2007. IEEE 11th International Conference on, pages 1-8. IEEE, 2007.
6. D. A. Clausi. An analysis of co-occurrence texture statistics as a function of grey level quantization. Canadian Journal of Remote Sensing, 28(1):45-62, 2002.
7. Pablo A. Estévez, Michel Tesmer, Claudio A. Perez, and Jacek M. Zurada. Normalized mutual information feature selection. Trans. Neur. Netw., 20(2):189-201, February 2009.
8. Pedro F Felzenszwalb and Daniel P Huttenlocher. Efficient graph-based image segmentation. International Journal of Computer Vision, 59(2):167-181, 2004.
9. Keinosuke Fukunaga. Introduction to Statistical Pattern Recognition (2nd Ed.). Academic Press Professional, Inc., San Diego, CA, USA, 1990.
10. Harald Ganster, Axel Pinz, Reinhard Röhrer, Ernst Wildling, Michael Binder, and Harald Kittler. Automated melanoma recognition. IEEE Trans. Med. Imaging, 20(3):233-239, 2001.
11. Rein-Lien Hsu, Mohamed Abdel-Mottaleb, and Anil K Jain. Face detection in color images. Pattern Analysis and Machine Intelligence, IEEE Transactions on, 24(5):696-706, 2002.
12. H. Y. Lee, W. Y. Chay, M. B. Tang, M. T. Chio, and S. H. Tan. Melanoma: Differences between asian and caucasian patients. Ann Acad Med Singapore, 41:17-20, 2012.
13. Huan Liu and Lei Yu. Toward integrating feature selection algorithms for classification and clustering. IEEE Trans. Knowl. Data Eng., 17(4):491-502, 2005.
14. Ilias Maglogiannis and Charalampos N. Doukas. Overview of advanced computer vision systems for skin lesions characterization. IEEE Transactions on Information Technology in Biomedicine, 13(5):721-733, 2009.
15. American Academy of Dermatology. What to look for: The abcde of melanoma. http://www.aad.org/spot-skin-cancer/understanding-skin-cancer/how-do-i-check-my-skin/what-to-look-for/, Accessed March 6, 2013.
16. Nobuyuki Otsu. A threshold selection method from gray-level histograms. Automatica, 11(285-296):23-27, 1975.
17. Hanchuan Peng, Fuhui Long, and Chris Ding. Feature selection based on mutual information: criteria of max-dependency, max-relevance, and min-redundancy. IEEE Transactions on Pattern Analysis and Machine Intelligence, 27:1226-1238, 2005.
18. Hanchuan Peng, Fuhui Long, and Chris Ding. Mrmr faq. http://penglab.janelia.org/proj/mRMR/FAQ-mrmr.htm/, Accessed March 6, 2013.
19. Kiran Ramlakhan and Yi Shang. A mobile automated skin lesion classification system. in ICTAI, pages 138-141, 2011.
20. Elisabetta La Torre, Tatiana Tommasi, Barbara Caputo, and Giovanni Ettore Gigante. Kernel methods for melanoma recognition. in MIE, pages 983-988, 2006.
21. Vladimir N. Vapnik. The Nature of Statistical Learning Theory. Springer-Verlag New York, Inc., New York, NY, USA, 1995.
22. T. Wadhawan, Ning Situ, Hu Rui, K. Lancaster, Xiaojing Yuan, and G. Zouridakis. Implementation of the 7-point checklist for melanoma detection on smart handheld devices. in Engineering in Medicine and Biology Society, pages 3180-3183. IEEE, 2011.
23. Fei Wang, Xin Wang, Daoqiang Zhang, Changshui Zhang, and Tao Li. marginface: A novel face recognition method by average neighborhood margin maximization. Pattern Recognition, 42(11):2863-2875, 2009.
24. K. Weismann, H. F. Lorentzen, C. Sand, and LEO Pharma. Dermoscopy. LEO Pharma, 2005.
25. L. Xu, M. Jackowski, A. Goshtasby, D. Roseman, S. Bines, C. Yu, A. Dhawan, and A. Huntley. Segmentation of skin cancer images. Image Vision Comput., 17(1):65-74, 1999.