Title :
An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images
Author :
Maglogiannis, I. ; Pavlopoulos, S. ; Koutsouris, D.
Author_Institution :
Dept. of Inf. & Commun. Syst. Eng., Univ. of Aegean, Samos, Greece
fDate :
3/1/2005 12:00:00 AM
Abstract :
This paper describes an integrated prototype computer-based system for the characterization of skin digital images. The first stage includes an image acquisition arrangement designed for capturing skin images, under reproducible conditions. The system processes the captured images and performs unsupervised image segmentation and image registration utilizing an efficient algorithm based on the log-polar transform of the images´ Fourier spectrum. Border- and color-based features, extracted from the digital images of skin lesions, were used to construct a classification module for the recognition of malignant melanoma versus dysplastic nevus. Different methods, drawn from the fields of artificial intelligence (neural networks) and statistical modeling (discriminant analysis), were used in order to find the best classification rules and to compare the results of different approaches to the problem.
Keywords :
feature extraction; image registration; image segmentation; medical image processing; neural nets; skin; Fourier spectrum; artificial intelligence; classification module; color-based features; dermatological images; discriminant analysis; dysplastic nevus; image acquisition; image analysis; image capturing; image registration; integrated computer supported acquisition; integrated prototype computer-based system; log-polar transform; malignant melanoma recognition; neural networks; pigmented skin lesion; skin digital images; statistical modeling; unsupervised image segmentation; Digital images; Feature extraction; Fourier transforms; Image recognition; Image registration; Image segmentation; Lesions; Pigmentation; Prototypes; Skin; Classification; image analysis; registration; segmentation; skin lesion; Algorithms; Artificial Intelligence; Colorimetry; Dysplastic Nevus Syndrome; Humans; Image Interpretation, Computer-Assisted; Melanoma; Pattern Recognition, Automated; Photography; Reproducibility of Results; Sensitivity and Specificity; Skin Neoplasms; Systems Integration; Video Recording;
Journal_Title :
Information Technology in Biomedicine, IEEE Transactions on
DOI :
10.1109/TITB.2004.837859