Myocardial Segmentation in MR images using fully Convolutional Neural Networks
(2018) In Master Thesis in Mathematical Sciences FMAM05 20172Mathematics (Faculty of Engineering)
- Abstract
- A convolutional neural network for automatic myocardial segmentation of MR images is described and implemented, based on the readily available architecture SegNet. A general network trained on both end-systolic and end-diastolic images is determined to be superior to the networks trained on the separate data. The evaluation of myocardial segmentation is discussed, as well as the importance of manual, visual inspection.
- Popular Abstract (Swedish)
- Detta arbete har undersökt hur ett neuralt nätverk bör tränas för att utlinjera hjärtmuskeln i MR-bilder. Med en begränsad mängd data såg vi hur man bör behandla sin data för att producera en välfungerande modell.
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/8960038
- author
- Nilsson, Mattias LU
- supervisor
- organization
- alternative title
- Utlinjering av hjärtmuskeln i MR-bilder med maskininlärning
- course
- FMAM05 20172
- year
- 2018
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- machine learning, artificial neural networks, convolutional neural networks, medical image analysis, image analysys, MRI, cardiac MRI, cardiac image analysis
- publication/series
- Master Thesis in Mathematical Sciences
- report number
- LUTFMA-3340-2018
- ISSN
- 1404-6342
- other publication id
- 2018:E6
- language
- English
- id
- 8960038
- date added to LUP
- 2018-12-28 14:36:09
- date last changed
- 2019-07-12 09:56:10
@misc{8960038, abstract = {{A convolutional neural network for automatic myocardial segmentation of MR images is described and implemented, based on the readily available architecture SegNet. A general network trained on both end-systolic and end-diastolic images is determined to be superior to the networks trained on the separate data. The evaluation of myocardial segmentation is discussed, as well as the importance of manual, visual inspection.}}, author = {{Nilsson, Mattias}}, issn = {{1404-6342}}, language = {{eng}}, note = {{Student Paper}}, series = {{Master Thesis in Mathematical Sciences}}, title = {{Myocardial Segmentation in MR images using fully Convolutional Neural Networks}}, year = {{2018}}, }