<abstract xmlns="http://www.w3.org/1999/xhtml"><p> Detecting the neural processes like axons and dendrites needs high quality SEM images. This paper proposes an approach using perceptual grouping via a graph cut and its combinations with Convolutional Neural Network (CNN) to achieve improved segmentation of SEM images. Experimental results demonstrate improved computational efficiency with linear running time.</p></abstract>

Detecting the neural processes like axons and dendrites needs high quality SEM images. This paper proposes an approach using perceptual grouping via a graph cut and its combinations with Convolutional Neural Network (CNN) to achieve improved segmentation of SEM images. Experimental results demonstrate improved computational efficiency with linear running time.

Enhanced CNN Based Electron Microscopy Image Segmentation

National Institute of Technology, Calicut, Kerala, India

Cybernetics and Information Technologies

{"article-title":"Enhanced CNN Based Electron Microscopy Image Segmentation"}

Detecting the neural processes like axons and dendrites needs high quality SEM images. This paper proposes an approach using perceptual grouping via a graph...

Enhanced CNN Based Electron Microscopy Image Segmentation

Data publikacji: 16 mar 2013

Zakres stron: 84 - 97

DOI: https://doi.org/10.2478/cait-2012-0014

Słowa kluczowe
Convolutional Neural Network, SEM image, perceptual grouping constraints via a graph cut, segmentation using a graph cut, graph cut optimization, affinity graph, backpropagation, Maxflow/Mincut algorithm, Neuronal segmentation

This content is open access.

Enhanced CNN Based Electron Microscopy Image Segmentation

Data publikacji: 16 mar 2013

Zakres stron: 84 - 97

DOI: https://doi.org/10.2478/cait-2012-0014

Słowa kluczoweConvolutional Neural Network, SEM image, perceptual grouping constraints via a graph cut, segmentation using a graph cut, graph cut optimization, affinity graph, backpropagation, Maxflow/Mincut algorithm, Neuronal segmentation

This content is open access.

Słowa kluczowe
Convolutional Neural Network, SEM image, perceptual grouping constraints via a graph cut, segmentation using a graph cut, graph cut optimization, affinity graph, backpropagation, Maxflow/Mincut algorithm, Neuronal segmentation