CADdy - Colposcopy learning machine for computer aided diagnosis
Traversi, M. ; Falagario, M. LU
and Guaragnella, C.
(2013)
2013 IEEE 3rd International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2013
2013-January.
- 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 colposcopic 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... (More)
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 colposcopic 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.
(Less)
- author
- Traversi, M.
; Falagario, M.
LU
and Guaragnella, C.
- publishing date
- 2013
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- keywords
- Cervix cancer, Colposcopy, Images processing, Machine learning, Neural network, Web application
- host publication
- Proceedings 2013 IEEE 3rd International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2013
- volume
- 2013-January
- article number
- 6697965
- pages
- 4 pages
- publisher
- IEEE Computer Society
- conference name
- 2013 IEEE 3rd International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2013
- conference location
- Berlin, Germany
- conference dates
- 2013-09-08 - 2013-09-11
- external identifiers
-
- scopus:85005962331
- ISBN
- 9781479914128
- DOI
- 10.1109/ICCE-Berlin.2013.6697965
- language
- English
- LU publication?
- no
- id
- 76101e76-c782-4b53-8cc3-93cf7a8ecb3f
- date added to LUP
- 2019-02-16 08:33:47
- date last changed
- 2022-01-31 17:43:10
@inproceedings{76101e76-c782-4b53-8cc3-93cf7a8ecb3f,
abstract = {{<p>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 colposcopic 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.</p>}},
author = {{Traversi, M. and Falagario, M. and Guaragnella, C.}},
booktitle = {{Proceedings 2013 IEEE 3rd International Conference on Consumer Electronics - Berlin, ICCE-Berlin 2013}},
isbn = {{9781479914128}},
keywords = {{Cervix cancer; Colposcopy; Images processing; Machine learning; Neural network; Web application}},
language = {{eng}},
publisher = {{IEEE Computer Society}},
title = {{CADdy - Colposcopy learning machine for computer aided diagnosis}},
url = {{http://dx.doi.org/10.1109/ICCE-Berlin.2013.6697965}},
doi = {{10.1109/ICCE-Berlin.2013.6697965}},
volume = {{2013-January}},
year = {{2013}},
}