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Deeply-Supervised Density Regression for Automatic Cell Counting in Microscopy Images
In this study, we proposed a new density regression-based method for automatically counting cells in microscopy images.
Automatic microscopic cell counting by use of deeply-supervised density regression model
Accurately counting cells in microscopic images is important for medical diagnoses and biological studies, but manual cell counting is very tedious, time-consuming, and prone to subjective errors, and automatic counting can be less accurate than desired.
Automatic microscopic cell counting by use of unsupervised adversarial domain adaptation and supervised density regression
A domain adaptation model (DAM) is built to map experimental images (the target domain) to the feature space of the source domain.
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