1 citations · 1 across the 1 of their papers we have counts for
3 papers
Region Growing with Convolutional Neural Networks for Biomedical Image Segmentation
John Lagergren, Erica Rutter, Kevin Flores
In this paper we present a methodology that uses convolutional neural networks (CNNs) for segmentation by iteratively growing predicted mask regions in each coordinate direction. T…
Biologically-informed neural networks guide mechanistic modeling from sparse experimental data
John H. Lagergren, John T. Nardini, Ruth E. Baker +2
Biologically-informed neural networks (BINNs), an extension of physics-informed neural networks [1], are introduced and used to discover the underlying dynamics of biological syste…
Learning Equations from Biological Data with Limited Time Samples
John T. Nardini, John H. Lagergren, Andrea Hawkins-Daarud +5
Equation learning methods present a promising tool to aid scientists in the modeling process for biological data. Previous equation learning studies have demonstrated that these me…