Quantitative Error Prediction of Medical Image Registration using Regression Forests

18 May 2019Hessam SokootiGorkem SaygiliBen GlockerBoudewijn P. F. LelieveldtMarius Staring

Predicting registration error can be useful for evaluation of registration procedures, which is important for the adoption of registration techniques in the clinic. In addition, quantitative error prediction can be helpful in improving the registration quality... (read more)

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