Machine learning in quantitative PET: A review of attenuation correction and low-count image reconstruction methods

Positron emission tomography (PET) has been used as a non-invasive functional imaging modality with a wide range of clinical applications. By providing the information of metabolic processes in the human body, it is utilized for various purposes including tumor staging and detection of metastases in oncology [1 –9], gross target volume definition in radiation oncology [10–12], myocardial perfusion in cardiology [13,14], and investigation of neurological disorders [15]. Among these applications, the accuracy of tracer uptake quantification has been less recognized than other characteristics of PET such as sensitivity [16].

Source: Physica Medica: European Journal of Medical Physics - July 28, 2020 Category: General Medicine Authors: Tonghe Wang, Yang Lei, Yabo Fu, Walter J. Curran, Tian Liu, Jonathon A. Nye, Xiaofeng Yang Tags: Review paper Source Type: research