Segmentation of Dense Cell Populations using Convolutional Neural Networks – Bc. Filip Lux
Bc. Filip Lux
Master's thesis
Segmentation of Dense Cell Populations using Convolutional Neural Networks
Segmentation of Dense Cell Populations using Convolutional Neural Networks
Abstract:
Diplomová práce se zabývá schopnostmi konvolučních neurálních sítí segmentovat mikroskopové snímky hustých buněčných populací. Pro výzkum byl zvolen datová množina obrazů ze soutěže Cell Tracking Challenge, který není snadné řešit tradičními technikami zpracování obrazu. Vytvořili jsme a natrénovali vlastní konvoluční neurání síť segmentující tyto snímky, která je úspěšná i v mezinárodním srovnání …moreAbstract:
This thesis examines the ability of convolutional neural networks to segment microscopy images of dense cell populations. We chose an image dataset from the Cell Tracking Challenge competition, which is not easy to solve using traditional image processing techniques. We built and trained our convolutional neural network able to segment these images, which is successful also in the international context …more
Language used: English
Date on which the thesis was submitted / produced: 21. 5. 2018
Identifier:
https://is.muni.cz/th/v35vy/
Thesis defence
- Date of defence: 18. 6. 2018
- Supervisor: doc. RNDr. Petr Matula, Ph.D.
- Reader: prof. RNDr. Michal Kozubek, Ph.D.
Citation record
Full text of thesis
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Institution archiving the thesis and making it accessible: Masarykova univerzita, Fakulta informatikyMasaryk University
Faculty of InformaticsMaster programme / field:
Informatics / Artificial Intelligence and Natural Language Processing
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