Tomographic back-projection of either sparse or low-quality projection views, based on convolutional neural networks (CNN) – Payal JAIN
Payal JAIN
Master's thesis
Tomographic back-projection of either sparse or low-quality projection views, based on convolutional neural networks (CNN)
Abstract:
This thesis delves into the integration of classical and modern approaches in tomographic back-projection, with a particular emphasis on challenges presented by sparse or low-quality projection views. The research is dedicated to advancing reconstruction methods by combining Convolutional Neural Networks (CNNs) with classical algorithms, specifically the Feldkamp-Davis-Kress (FDK) and Simultaneous …moreAbstract:
This thesis delves into the integration of classical and modern approaches in tomographic back-projection, with a particular emphasis on challenges presented by sparse or low-quality projection views. The research is dedicated to advancing reconstruction methods by combining Convolutional Neural Networks (CNNs) with classical algorithms, specifically the Feldkamp-Davis-Kress (FDK) and Simultaneous …more
Language used: English
Date on which the thesis was submitted / produced: 9. 2. 2024
Thesis defence
- Supervisor: prof. Dr. Simon Zabler
Citation record
ISO 690-compliant citation record:
JAIN, Payal. \textit{Tomographic back-projection of either sparse or low-quality projection views, based on convolutional neural networks (CNN)}. Online. Master's thesis. České Budějovice: University of South Bohemia in České Budějovice, Faculty of Science. 2024. Available from: https://theses.cz/id/m9or5p/.
The right form of listing the thesis as a source quoted
JAIN, Payal. Tomographic back-projection of either sparse or low-quality projection views, based on convolutional neural networks (CNN). České Budějovice, 2024. diplomová práce (Mgr.). JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH. Přírodovědecká fakulta
Full text of thesis
Contents of on-line thesis archive
Published in Theses:- Soubory jsou nedostupné do 9. 2. 2027
- Po tomto datu bude práce dostupná: světu
Other ways of accessing the text
Institution archiving the thesis and making it accessible: JIHOČESKÁ UNIVERZITA V ČESKÝCH BUDĚJOVICÍCH, Přírodovědecká fakultaUNIVERSITY OF SOUTH BOHEMIA IN ČESKÉ BUDĚJOVICE
Faculty of ScienceMaster programme / field:
Artificial Intelligence and Data Science / Artificial Intelligence and Data Science
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