Title :
CADdy — Colposcopy learning machine for computer aided diagnosis
Author :
Traversi, M. ; Falagario, M. ; Guaragnella, C.
Author_Institution :
DEI - Dept. of Electrics and Information, Polytechnic University of Bari, Italy
Abstract :
The study and development of a decision support system for doctors and students is presented, aiming to ease the diagnosis of the cervix cancer through an automated smart system: using a web application, a medical expert can upload colposcopie images feeding an expert system that carries out a deep analysis by a processing system on images uploaded by doctors; results coming out of the processing system are presented by a user friendly system suggesting the decision to the the medical expert who is able to confirm or change it, and annotate information. If changed, the diagnosis is sent to the expert system, developed on a reinforcement learning scheme, to tune decision parameters and enhance detection rates. The paper present the work in progress preliminary results of the system being developed.
Keywords :
IEEE Xplore; Portable document format; Machine learning; cervix cancer; colposcopy; images processing; neural network; web application;
Conference_Titel :
Consumer Electronics ?? Berlin (ICCE-Berlin), 2013. ICCEBerlin 2013. IEEE Third International Conference on
Conference_Location :
Berlin
Print_ISBN :
978-1-4799-1411-1
DOI :
10.1109/ICCE-Berlin.2013.6697965