DocumentCode :
672030
Title :
Artificial prediction markets for lymph node detection
Author :
Barbu, Andrei ; Lay, N.
Author_Institution :
Stat. Dept., Florida State Univ., Tallahassee, FL, USA
fYear :
2013
fDate :
21-23 Nov. 2013
Firstpage :
1
Lastpage :
7
Abstract :
Prediction markets are forums aimed at predicting the outcome of future events of interest such as election results. People participate in a prediction market by buying contracts on the possible outcomes. They are rewarded after the outcome is known based on the number of contracts purchased for the correct outcome. The Artificial Prediction Market is a novel machine learning method that simulates a prediction market where the participants are trained classifiers instead of people. In this work we present an application of the Artificial Prediction Market to lymph node detection from CT images. An evaluation on 54 CT volumes shows that the detector trained with the Artificial Prediction Market has a detection rate of 81.2% at 3 false positives per volume, while an Adaboost classifier trained on the same features obtains a detection rate of 79.6% at the same false positive rate.
Keywords :
computerised tomography; image segmentation; learning (artificial intelligence); medical image processing; CT imaging; CT volumes; adaboost classifier; artificial prediction markets; false positive rate; lymph node detection; machine learning method; trained classifiers; Computed tomography; Feature extraction; Image segmentation; lymph node detection; medical imaging; prediction markets;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
E-Health and Bioengineering Conference (EHB), 2013
Conference_Location :
Iasi
Print_ISBN :
978-1-4799-2372-4
Type :
conf
DOI :
10.1109/EHB.2013.6707376
Filename :
6707376
Link To Document :
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