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IBBM / Cascaded-FCN

Source code for the MICCAI 2016 Paper "Automatic Liver and Lesion Segmentation in CT Using Cascaded Fully Convolutional NeuralNetworks and 3D Conditional Random Fields"
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Discrepancy in dice scores #7

Closed kiranvaidhya closed 7 years ago

kiranvaidhya commented 7 years ago

You have reported a dice score of 82.3% for the lesions in the first paper. It's not clear as to what this metric belongs to. Is it the dice score for lesion at training or testing?

In the follow-up paper, it's been reported as follows: "In general, we observe significant additional improvements for Dice overlaps of liver segmentations, from mean Dice 93.1% to 94.3% after applying the 3D CRF. For lesions we could achieve a Dice score of 56% at a standard deviation of 26% with a 2 fold cross-validation."

Can you clarify me regarding the correct results? Why is there a discrepancy?

PatrickChrist commented 7 years ago

Thanks for asking. The dice score of 82.3% in the first paper is referring to figure 1. The dice score of the final slice is 82% dice. In the follow-up paper we report mean dice over volumes with a 2 fold cross validation.