GHEZAL Ali

Optimal processing for gel electrophoresis images: Applying Monte Carlo Tree Search in GelApp

In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the image processing algorithm.

type: 
Journal Paper
journal: 
Electrophoresis 2016, 10.1002/elps.201600197
Url: 
http://onlinelibrary.wiley.com/doi/10.1002/elps.201600197/full
Impact Factor: 
3.028
Date of acceptance: 
2016-05-23

Optimal processing for gel electrophoresis images: Applying Monte Carlo Tree Search in GelApp

In biomedical research, gel band size estimation in electrophoresis analysis is a routine process. To facilitate and automate this process, numerous software have been released, notably the GelApp mobile app. However, the band detection accuracy is limited due to a band detection algorithm that cannot adapt to the variations in input images. To address this, we used the Monte Carlo Tree Search with Upper Confidence Bound (MCTS-UCB) method to efficiently search for optimal image processing pipelines for the band detection task, thereby improving the image processing algorithm.

type: 
Journal Paper
journal: 
Electrophoresis 2016, 10.1002/elps.201600197
pubmed: 
http://onlinelibrary.wiley.com/doi/10.1002/elps.201600197/full
Url: 
http://onlinelibrary.wiley.com/doi/10.1002/elps.201600197/full
Impact Factor: 
2.482
Date of acceptance: 
2016-06-20
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