Multi-set multi-temporal canonical analysis of psoriasis images |
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| Abstract | Nowadays, the medical tracking of dermatological diseases is imprecise, mainly due to the lack of suitable objective methods to evaluate the lesion. The severity of the disease is currently scored by doctors merely by means of visual examination. In this work, multi-set canonical correlation analysis over registered images is proposed to track the evolution of the disease automatically. This method transforms the original images into sets of variables that exhibit decreasing degree of similarity, based on correlation measures. Due to this property, these new variables are more suitable to detect where changes occur. An experiment with 5 different time series collected from psoriasis patients during 4 different sessions is conducted. The analysis of the obtained results points out some patterns that can be used both to interpret and summarize the evolution of the lesion and to achieve a better image registration. |
| Keywords | multiset canonical correlation analysis, image registration, psoriasis |
| Type | Conference paper [With referee] |
| Conference | IEEE International Symposium on Biomedical Imaging |
| Year | 2004 Month April pp. 1151-1154 |
| Address | Richard Petersens Plads, Building 321 |
| Series | Technical University of Denmark |
| Electronic version(s) | [pdf] |
| BibTeX data | [bibtex] |
| IMM Group(s) | Image Analysis & Computer Graphics |