Transformation of PET raw data into images for event classification using convolutional neural networks

Transformation of PET raw data into images for event classification using convolutional neural networks

In positron emission tomography (PET) studies, convolutional neural networks (CNNs) may be applied directly to the reconstructed distribution of radioactive tracers injected into the patient's body, as a pattern recognition tool. Nonetheless, unprocessed PET coincidence data exist in tabular fo...

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Bibliographic Details
Main Authors: Paweł Konieczka, Lech Raczyński, Wojciech Wiślicki, Oleksandr Fedoruk, Konrad Klimaszewski, Przemysław Kopka, Wojciech Krzemień, Roman Y. Shopa, Jakub Baran, Aurélien Coussat, Neha Chug, Catalina Curceanu, Eryk Czerwiński, Meysam Dadgar, Kamil Dulski, Aleksander Gajos, Beatrix C. Hiesmayr, Krzysztof Kacprzak, Łukasz Kapłon, Grzegorz Korcyl, Tomasz Kozik, Deepak Kumar, Szymon Niedźwiecki, Szymon Parzych, Elena Pérez del Río, Sushil Sharma, Shivani Shivani, Magdalena Skurzok, Ewa Łucja Stępień, Faranak Tayefi, Paweł Moskal
Format: Article
Language:English
Published: AIMS Press 2023-07-01
Series:Mathematical Biosciences and Engineering
Subjects:
positron emission tomography
convolutional neural network
kernel principal component analysis
medical imaging
Online Access:https://www.aimspress.com/article/doi/10.3934/mbe.2023669?viewType=HTML

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https://www.aimspress.com/article/doi/10.3934/mbe.2023669?viewType=HTML

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