MPEG-7 visual descriptors selection for burn characterization by multidimensional scaling match

This paper presents a new approach towards the selection of color image features to be used in the classification of burn wounds. The features are selected such that they generate similarity matrices and multidimensional scaling (MDS) plots that match the similarity matrix and the MDS-plot resulting from a subjective visual burn area similarity test performed by trained surgeons. We show that standard MPEG-7 visual descriptors that combine color and texture are good candidates for the task of burn wound grading.

[1]  Chandan Chakraborty,et al.  Automated Tissue Classification Framework for Reproducible Chronic Wound Assessment , 2014, BioMed research international.

[2]  Sansanee Auephanwiriyakul,et al.  Automatic segmentation and degree identification in burn color images , 2012, The 4th 2011 Biomedical Engineering International Conference.

[3]  Aleksandra Mojsilovic,et al.  The vocabulary and grammar of color patterns , 2000, IEEE Trans. Image Process..

[4]  Begoña Acha,et al.  Classification of burn wounds using support vector machines , 2004, SPIE Medical Imaging.

[5]  Corneliu Florea,et al.  Severe burns assessment by joint color-thermal imagery and ensemble methods , 2016, 2016 IEEE 18th International Conference on e-Health Networking, Applications and Services (Healthcom).

[6]  Özgür Ulusoy,et al.  Bilvideo-7: an MPEG-7- compatible video indexing and retrieval system , 2010 .

[7]  Christine Fernandez-Maloigne,et al.  Correlating human color similarity judgments and colorimetric representations , 2003, Saratov Fall Meeting.

[8]  Trevor F. Cox,et al.  Metric multidimensional scaling , 2000 .

[9]  Johannes Dirnberger,et al.  Medical documentation of burn injuries , 2012 .

[10]  Marina Kolesnik,et al.  Multi-dimensional Color Histograms for Segmentation of Wounds in Images , 2005, ICIAR.

[11]  Begoña Acha,et al.  Burn Depth Analysis Using Multidimensional Scaling Applied to Psychophysical Experiment Data , 2013, IEEE Transactions on Medical Imaging.

[12]  Jeffrey W. Shupp,et al.  Critical Review of Burn Depth Assessment Techniques: Part I. Historical Review , 2009, Journal of burn care & research : official publication of the American Burn Association.

[13]  Naiem Moiemen,et al.  A pilot evaluation study of high resolution digital thermal imaging in the assessment of burn depth. , 2013, Burns : journal of the International Society for Burn Injuries.

[14]  Derek C. Rose,et al.  Deep Machine Learning - A New Frontier in Artificial Intelligence Research [Research Frontier] , 2010, IEEE Computational Intelligence Magazine.

[15]  Begoña Acha,et al.  Segmentation and classification of burn color images , 2001, 2001 Conference Proceedings of the 23rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[16]  Joseph L. Zinnes,et al.  Theory and Methods of Scaling. , 1958 .