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Team: Technische Universitat Munchen, Computer Aided Medical Procedure (CAMP), Munich, Germany

Authors: Bharti Munjal, Amil George, Shadi Albarqouni, Stefanie Demirci, Nassir Navab

Abstract:

The system uses two GoogleNet models trained on levels 6 and 3 respectively. Then, few geometric features are extracted from the response maps, i.e. Area, Orientation, Major/Minor Axis Length, statistical features (max, min, and mean) and fed to a random forest to predict the probability of a slide having a metastasis.

Results:

The following figure shows the receiver operating characteristic (ROC) curve of the method.

 

The following figure shows the free-response receiver operating characteristic (FROC) curve of the method.

 

The table below presents the average sensitivity of the developed system at 6 predefined false positive rates: 1/4, 1/2, 1, 2, 4, and 8 FPs per whole slide image.

FPs/WSI0.250.51248
Sensitivity0.2130.2400.2580.2760.2980.356


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