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Pseudo-Labeling Enhanced by Privileged Information and Its Application to In Situ Sequencing Images
Various strategies for label-scarce object detection have been explored by the computer vision research community.
Nucleus segmentation across imaging experiments: the 2018 Data Science Bowl
Segmenting the nuclei of cells in microscopy images is often the first step in the quantitative analysis of imaging data for biological and biomedical applications.
Automatic Renal Segmentation in DCE-MRI using Convolutional Neural Networks
In this paper, we propose a time and memory efficient fully automated segmentation method which achieves high segmentation accuracy with running time in the order of seconds in both normal kidneys and kidneys with hydronephrosis.
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