dc.contributor.author |
Maglogiannis, I |
en |
dc.contributor.author |
Pavlopoulos, S |
en |
dc.contributor.author |
Koutsouris, D |
en |
dc.date.accessioned |
2014-03-01T01:21:49Z |
|
dc.date.available |
2014-03-01T01:21:49Z |
|
dc.date.issued |
2005 |
en |
dc.identifier.issn |
1089-7771 |
en |
dc.identifier.uri |
https://dspace.lib.ntua.gr/xmlui/handle/123456789/16389 |
|
dc.subject |
Classification |
en |
dc.subject |
Image analysis |
en |
dc.subject |
Registration |
en |
dc.subject |
Segmentation |
en |
dc.subject |
Skin lesion |
en |
dc.subject.classification |
Computer Science, Information Systems |
en |
dc.subject.classification |
Computer Science, Interdisciplinary Applications |
en |
dc.subject.classification |
Mathematical & Computational Biology |
en |
dc.subject.classification |
Medical Informatics |
en |
dc.subject.other |
Algorithms |
en |
dc.subject.other |
Artificial intelligence |
en |
dc.subject.other |
Data acquisition |
en |
dc.subject.other |
Dermatology |
en |
dc.subject.other |
Feature extraction |
en |
dc.subject.other |
Fourier transforms |
en |
dc.subject.other |
Image segmentation |
en |
dc.subject.other |
Mathematical models |
en |
dc.subject.other |
Neural networks |
en |
dc.subject.other |
Skin |
en |
dc.subject.other |
Statistical methods |
en |
dc.subject.other |
Image registration |
en |
dc.subject.other |
Skin lesion |
en |
dc.subject.other |
Image analysis |
en |
dc.subject.other |
algorithm |
en |
dc.subject.other |
article |
en |
dc.subject.other |
artificial intelligence |
en |
dc.subject.other |
automated pattern recognition |
en |
dc.subject.other |
clinical trial |
en |
dc.subject.other |
colorimetry |
en |
dc.subject.other |
comparative study |
en |
dc.subject.other |
computer assisted diagnosis |
en |
dc.subject.other |
dysplastic nevus |
en |
dc.subject.other |
human |
en |
dc.subject.other |
melanoma |
en |
dc.subject.other |
methodology |
en |
dc.subject.other |
pathology |
en |
dc.subject.other |
photography |
en |
dc.subject.other |
reproducibility |
en |
dc.subject.other |
sensitivity and specificity |
en |
dc.subject.other |
skin tumor |
en |
dc.subject.other |
system analysis |
en |
dc.subject.other |
videorecording |
en |
dc.subject.other |
Algorithms |
en |
dc.subject.other |
Artificial Intelligence |
en |
dc.subject.other |
Colorimetry |
en |
dc.subject.other |
Dysplastic Nevus Syndrome |
en |
dc.subject.other |
Humans |
en |
dc.subject.other |
Image Interpretation, Computer-Assisted |
en |
dc.subject.other |
Melanoma |
en |
dc.subject.other |
Pattern Recognition, Automated |
en |
dc.subject.other |
Photography |
en |
dc.subject.other |
Reproducibility of Results |
en |
dc.subject.other |
Sensitivity and Specificity |
en |
dc.subject.other |
Skin Neoplasms |
en |
dc.subject.other |
Systems Integration |
en |
dc.subject.other |
Video Recording |
en |
dc.title |
An integrated computer supported acquisition, handling, and characterization system for pigmented skin lesions in dermatological images |
en |
heal.type |
journalArticle |
en |
heal.identifier.primary |
10.1109/TITB.2004.837859 |
en |
heal.identifier.secondary |
http://dx.doi.org/10.1109/TITB.2004.837859 |
en |
heal.language |
English |
en |
heal.publicationDate |
2005 |
en |
heal.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. © 2005 IEEE. |
en |
heal.publisher |
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC |
en |
heal.journalName |
IEEE Transactions on Information Technology in Biomedicine |
en |
dc.identifier.doi |
10.1109/TITB.2004.837859 |
en |
dc.identifier.isi |
ISI:000227676200011 |
en |
dc.identifier.volume |
9 |
en |
dc.identifier.issue |
1 |
en |
dc.identifier.spage |
86 |
en |
dc.identifier.epage |
98 |
en |