Source codes:

FourierNet : Shape-preserving network for medical image segmentation
EM-Estimator : Deep learning-enabled electromagnetic near-field prediction and inverse design of metasurfaces
MTFD-Net : Left atrium segmentation through fractal dimension estimation
DeepDistance : A multi-task deep regression model for cell detection in inverted microscopy images
AttentionBoost : Learning what to attend by boosting fully convolutional networks
DeepFeature : Unsupervised feature extraction via deep learning for histopathological images
ObjectOriented : Object oriented segmentation of cell nuclei in fluorescence microscopy images
Iter-hMin : Iterative h-minima based marker-controlled watershed for cell nucleus segmentation
GraphRLM : Graph run-length matrices for unsupervised segmentation of histopathological images
Circle-fit : Algorithm for locating circles on a set of pixels (need to modify the GraphRLM source codes)


NucleusSegData : Cell nucleus segmentation dataset for fluorescence microscopy images