3D PET image reconstruction based on the maximum likelihood estimation method (MLEM) algorithm
Year: 2014
Type: article
Abstract: A positron emission tomography (PET) scan does not measure an image directly. Instead, a PET scan measures a sinogram at the boundary of the field-of-view that consists of measurements of the sums of all the counts along the lines connecting the two detectors. Because there is a multitude of detectors built in a typical PET structure, there are many possible detector pairs that pertain to the measurement. The problem is how to turn this measurement into an image (this is called imaging). Significant improvement in PET image quality was achieved with the introduction of iterative reconstruction techniques. This was realized approximately 20 years ago (with the advent of new powerful computing processors). However, three-dimensional imaging still remains a challenge. The purpose of the image reconstruction algorithm is to process this imperfect count data for a large number (many millions) of lines of response and millions of detected photons to produce an image showing the distribution of the labeled molecules in space.
Source: Bio-Algorithms and Med-Systems
Authors: Artur Słomski, Zbigniew Rudy, Tomasz Bednarski, Piotr Białas, Eryk Czerwiński, Łukasz Kapłon, Andrzej Kochanowski, Grzegorz Korcyl, Jakub Kowal, Paweł Kowalski, Tomasz Kozik, Wojciech Krzemień, Marcin Molenda, Paweł Moskal, Szymon Niedźwiecki, Marek Pałka, Monika Pawlik, Lech Raczyński, Piotr Salabura, Neha Gupta-Sharma, Michał Silarski, Jerzy Smyrski, Adam Strzelecki, Wojciech Wiślicki, Marcin Zieliński, Natalia Zoń
Institutions: Jagiellonian University, National Centre for Nuclear Research
Language: English
Subfield: Radiology, Nuclear Medicine and Imaging
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W2168242542