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Fig. 3 | European Radiology Experimental

Fig. 3

From: Automatic lung segmentation in routine imaging is primarily a data diversity problem, not a methodology problem

Fig. 3

Ground truth annotations in public datasets lack coverage of pathologic areas. Segmentation results for cases in public datasets where the masks generated by our U-net(R-231) yielded low Dice similarity coefficients when compared to the ground truth. Note that public datasets often do not include high-density areas in the segmentations. Tumours in the lung area should be included in the segmentation while the liver should not

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