Title :
Segmentation of oct skin images by classification of speckle statistical parameters
Author :
Ali, Mcheik ; Hadj, Batatia
Author_Institution :
Univ. of Toulouse, Toulouse, France
Abstract :
This paper deals with segmentation of dermatological OCT images. Classic image segmentation techniques fail to produce accurate results due to the wide presence of speckle. We propose using speckle as source of information in the segmentation process. Different statistical models are analyzed in terms of their ability to differentiate skin layers. The local speckle parameters are used as a features-vector to classify, in a supervised way, different regions. Experimental results are presented using a corpus of twenty three real images delineated by experts. These confirm the potential of the method to generate useful data for robust segmentation.
Keywords :
image classification; image segmentation; medical image processing; optical tomography; skin; statistical analysis; vectors; OCT skin image; dermatological OCT images; features-vector; image classification; image segmentation; local speckle parameter; optical coherence tomography; speckle statistical parameter; Adaptive optics; Epidermis; Image segmentation; Nakagami distribution; Pixel; Speckle; OCT; segmentation; speckle modeling; tissue characterization;
Conference_Titel :
Image Processing (ICIP), 2010 17th IEEE International Conference on
Conference_Location :
Hong Kong
Print_ISBN :
978-1-4244-7992-4
Electronic_ISBN :
1522-4880
DOI :
10.1109/ICIP.2010.5653019