Εξειδίκευση τύπου :	Άρθρο σε επιστημονικό περιοδικό
Τίτλος:	A collaborative biomedical image-mining framework: Application on the image analysis of microscopic kidney biopsies
Δημιουργός/Συγγραφέας:	Goudas T. Doukas C. [EL] Χατζηιωάννου, Αριστοτέλης[EN] Chatziioannou, Aristotelis Maglogiannis I.
Ημερομηνία:	2013
Γλώσσα:	Αγγλικά
ISSN:	2168-2194
DOI:	10.1109/TITB.2012.2224666
Άλλο:	PubMed ID: 23076078
Περίληψη:	The analysis and characterization of biomedical image data is a complex procedure involving several processing phases, such as data acquisition, preprocessing, segmentation, feature extraction, and classification. The proper combination and parameterization of the utilized methods are heavily relying on the given image dataset and experiment type. They may thus necessitate advanced image processing and classification knowledge and skills from the side of the biomedical expert. In this study, an application, exploiting web services and applying ontological modeling, is presented, to enable the intelligent creation of image-mining workflows. The described tool can be directly integrated to the RapidMiner, Taverna or similar workflow management platforms. A case study dealing with the creation of a sample workflow for the analysis of kidney biopsy microscopy images is presented to demonstrate the functionality of the proposed framework.
Τίτλος πηγής δημοσίευσης:	IEEE Journal of Biomedical and Health Informatics
Τόμος/Κεφάλαιο:	17
Τεύχος:	1
Σελίδες:	82-91
Θεματική Κατηγορία:	[EL] Ιατρική (Γενικά)[EN] Medicine (General) [EL] Τεχνολογία (Γενικά)[EN] Technology (General)
Λέξεις-Κλειδιά:	Classification Image microscopy Image mining Intelligent planning Kidney biopsies Workflow manager
Αξιολόγηση από ομότιμους (peer reviewed):	Ναι
Κάτοχος πνευματικών δικαιωμάτων:	© 2012 IEEE.
Εμφανίζεται στις συλλογές:	Ινστιτούτο Χημικής Βιολογίας - Επιστημονικό έργο