AI Medical Compendium Journal:
European journal of nuclear medicine and molecular imaging

Showing 31 to 40 of 112 articles

Deep learning for improving PET/CT attenuation correction by elastic registration of anatomical data.

European journal of nuclear medicine and molecular imaging
BACKGROUND: For PET/CT, the CT transmission data are used to correct the PET emission data for attenuation. However, subject motion between the consecutive scans can cause problems for the PET reconstruction. A method to match the CT to the PET would...

Low-count whole-body PET/MRI restoration: an evaluation of dose reduction spectrum and five state-of-the-art artificial intelligence models.

European journal of nuclear medicine and molecular imaging
PURPOSE: To provide a holistic and complete comparison of the five most advanced AI models in the augmentation of low-dose F-FDG PET data over the entire dose reduction spectrum.

Decentralized collaborative multi-institutional PET attenuation and scatter correction using federated deep learning.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction and scatter compensation (AC/SC) are two main steps toward quantitative PET imaging, which remain challenging in PET-only and PET/MRI systems. These can be effectively tackled via deep learning (DL) methods. However, t...

Predicting clinically significant prostate cancer with a deep learning approach: a multicentre retrospective study.

European journal of nuclear medicine and molecular imaging
PURPOSE: This study aimed to develop deep learning (DL) models based on multicentre biparametric magnetic resonance imaging (bpMRI) for the diagnosis of clinically significant prostate cancer (csPCa) and compare the performance of these models with t...

Multi-center, multi-vendor validation of deep learning-based attenuation correction in SPECT MPI: data from the international flurpiridaz-301 trial.

European journal of nuclear medicine and molecular imaging
PURPOSE: Although SPECT myocardial perfusion imaging (MPI) is susceptible to artifacts from soft tissue attenuation, most scans are performed without attenuation correction. Deep learning-based attenuation corrected (DLAC) polar maps improved diagnos...

Mitigating bias in deep learning for diagnosis of coronary artery disease from myocardial perfusion SPECT images.

European journal of nuclear medicine and molecular imaging
PURPOSE: Artificial intelligence (AI) has high diagnostic accuracy for coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, when trained using high-risk populations (such as patients with correlating invasive testing), the ...

Polar map-free 3D deep learning algorithm to predict obstructive coronary artery disease with myocardial perfusion CZT-SPECT.

European journal of nuclear medicine and molecular imaging
PURPOSE: Deep learning (DL) models have been shown to outperform total perfusion deficit (TPD) quantification in predicting obstructive coronary artery disease (CAD) from myocardial perfusion imaging (MPI). However, previously published methods have ...

Quantitative evaluation of a deep learning-based framework to generate whole-body attenuation maps using LSO background radiation in long axial FOV PET scanners.

European journal of nuclear medicine and molecular imaging
PURPOSE: Attenuation correction is a critically important step in data correction in positron emission tomography (PET) image formation. The current standard method involves conversion of Hounsfield units from a computed tomography (CT) image to cons...

Application of artificial intelligence in nuclear medicine and molecular imaging: a review of current status and future perspectives for clinical translation.

European journal of nuclear medicine and molecular imaging
Artificial intelligence (AI) will change the face of nuclear medicine and molecular imaging as it will in everyday life. In this review, we focus on the potential applications of AI in the field, both from a physical (radiomics, underlying statistics...