Title
A combined alignment and registration scheme of lesions with psoriasis
Abstract
A scheme that registers and aligns digital image lesions of psoriasis within and between sessions is proposed. Lesions to be tracked are found under the assumption of being the object of largest size in thematic maps produced by a two-step hierarchical classification scheme that uses the output of an expectation-maximization algorithm to obtain a classification window of optimal size. Advantage is taken of the fact that the shape and the size of lesions with psoriasis do not change very much along the time. A first alignment of the lesions is done assuming that the correspondence between points is given by equivalence of positions of pixels after translations and rotations. Finally, a combined contextual registration and alignment scheme is applied. The alignment and registration schemes both use an Extreme Value Detection Algorithm based on a retinal mapping model. The output of the scheme is satisfactory not only in terms of visual appreciation of the aligned lesions, but also because the variation within sessions in the aligned lesions resembles randomly distributed Gaussian noise.
Year
DOI
Venue
2005
10.1016/j.ins.2005.01.009
Inf. Sci.
Keywords
Field
DocType
largest size,two-step hierarchical classification scheme,aligns digital image lesion,classification window,registration scheme,alignment scheme,combined contextual registration,combined alignment,gaussian noise,optimal size,extreme value detection algorithm,digital image,extreme value,expectation maximization algorithm,thematic maps,expectation maximization
Computer vision,Pattern recognition,Expectation–maximization algorithm,Extreme value theory,Classification scheme,Digital image,Equivalence (measure theory),Artificial intelligence,Pixel,Gaussian noise,Machine learning,Mathematics
Journal
Volume
Issue
ISSN
175
3
0020-0255
Citations 
PageRank 
References 
5
0.66
2
Authors
3
Name
Order
Citations
PageRank
G. Maletti150.66
Bjarne Ersbøll245038.06
Knut Conradsen331132.35