Microscopy images segmentation algorithm based on shearlet neural network

Microscopic images are becoming important and need to be studied know the details how-to quantitatively evaluate decellularization. Most of existing research focuses on deep learning-based techniques that lack simplification for A new computational method segmentation microscopy based shearlet neural network (SNN) has been introduced. The proposal is link concept shearlets transform networks into a single unit. contains feed-forward uses hidden layer. activation functions depending standard transform. proposed SNN powerful technology segmenting an electron microscopic image trained without relying pre-information data. capture features full accuracy contextual information, respectively. expected value specific inputs estimated by learning functional configuration sequence observed value. Experimental results two-dimensional promising confirm benefits approach. Lastly, we investigate challenging datasets ISBI 2012 our achieves superior outcomes when compared classical methods.