Influence of uncertainty estimation techniques on false-positive reduction in liver lesion detection. (arXiv:2206.10911v1 [eess.IV])

Deep learning techniques show success in detecting objects in medical images,
but still suffer from false-positive predictions that may hinder accurate
diagnosis. The estimated uncertainty of the neural network output has been used
to flag incorrect predictions. We study the role played by features computed
from neural network uncertainty estimates and shape-based features computed
from binary predictions in reducing false positives in liver lesion detection
by developing a classification-based post-processing step for different
uncertainty estimation methods. We demonstrate an improvement …

arxiv detection false false-positive influence positive uncertainty