Authors:
M. E. Fantacci
1
;
2
;
A. Traverso
3
;
4
;
S. Bagnasco
4
;
C. Bracco
5
;
D. Campanella
5
;
G. Chiara
5
;
E. Lopez Torres
4
;
6
;
A. Manca
5
;
D. Regge
5
;
M. Saletta
4
;
M. Stasi
5
;
S. Vallero
4
;
L. Vassallo
5
and
P. Cerello
4
Affiliations:
1
University of Pisa, Italy
;
2
Sezione di Pisa, Italy
;
3
Polytechnic University of Turin, Italy
;
4
Sezione di Torino, Italy
;
5
Candiolo Cancer Institute - FPO, IRCCS, Italy
;
6
CEADEN, Cuba
Keyword(s):
Web Service, Cloud Computing, Computer Aided Detection, Lung Nodules.
Abstract:
M5L, a Web-based Computer-Aided Detection (CAD) system to automatically detect lung nodules in thoracic Computed Tomographies, is based on a multi-thread analysis by independent subsystems and the combination of their results. The validation on 1043 scans of 3 independent data-sets showed consistency across data-sets, with a sensitivity of about 80% in the 4-8 range of False Positives per scan, despite varying acquisition and reconstruction parameters and annotation criteria. To make M5L CAD available to users without hardware or software new installations and configuration, a Software as a Service (SaaS) approach was adopted. A web front-end handles the work (image upload, results notification and direct on-line annotation by radiologists) and the communication with the OpenNebula-based cloud infrastructure, that allocates virtual computing and storage resources. The exams uploaded through the web interface are anonymised and analysis is performed in an isolated and independent clou
d environment. The average processing time for case is about 20 minutes and up to 14 cases can be processed in parallel. Preliminary results on the on-going clinical validation shows that the M5L CAD adds 20% more nodules originally overlooked by radiologists, allowing a remarkable increase of the overall detection sensitivity.
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