GHEZAL Ali

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

Published date : 02 Jun 2016

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
Impact Factor
2.482

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

Published date : 02 Jun 2016

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
Impact Factor
3.028