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Found 4 papers, 0 papers with code
Morphology on categorical distributions
The categorical distribution is a natural representation of uncertainty in multi-class segmentations.
A small note on variation in segmentation annotations
We report on the results of a small crowdsourcing experiment conducted at a workshop on machine learning for segmentation held at the Danish Bio Imaging network meeting 2020.
Learning to quantify emphysema extent: What labels do we need?
We evaluate performance on 600 low-dose CT scans from the Danish Lung Cancer Screening Trial and find that learning from emphysema presence labels, which are much easier to obtain, gives equally good performance to learning from emphysema extent labels.
Feature learning based on visual similarity triplets in medical image analysis: A case study of emphysema in chest CT scans
We evaluate the networks on 973 images, and show that the CNNs can learn disease relevant feature representations from derived similarity triplets.
