Micro-Net: A unified model for segmentation of various objects in microscopy images

Understand

Object segmentation and structure localization are important steps in automated image analysis pipelines for microscopy images.

• We present a convolution neural network (CNN) based deep learning architecture for segmentation of objects in microscopy images.
• The proposed network can be used to segment cells, nuclei and glands in fluorescence microscopy and histology images after slight tuning of input parameters.
• The network trains at multiple resolutions of the input image, connects the intermediate layers for better localization and context and generates the output using multi-resolution deconvolution filters.