Segmentation-Consistent Probabilistic Lesion Counting. (arXiv:2204.05276v2 [eess.IV] UPDATED)

Web: http://arxiv.org/abs/2204.05276

Lesion counts are important indicators of disease severity, patient
prognosis, and treatment efficacy, yet counting as a task in medical imaging is
often overlooked in favor of segmentation. This work introduces a novel
continuously differentiable function that maps lesion segmentation predictions
to lesion count probability distributions in a consistent manner. The proposed
end-to-end approach--which consists of voxel clustering, lesion-level voxel
probability aggregation, and Poisson-binomial counting--is non-parametric and
thus offers a robust and consistent way to augment lesion segmentation models
with …

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