PURPOSE: The deep learning time-of-flight (DL-ToF) aims to replicate the ToF effects through post-processing, applying deep learning-based enhancement to PET images. This study evaluates the effectiveness of DL-ToF using a chest-abdomen phantom that ...
Alzheimer's disease (AD) is a chronic neurodegenerative disorder with a global impact. The past few decades have witnessed significant strides in comprehending the underlying pathophysiological mechanisms and developing diagnostic methodologies for A...
Background PET can be used for amyloid-tau-neurodegeneration (ATN) classification in Alzheimer disease, but incurs considerable cost and exposure to ionizing radiation. MRI currently has limited use in characterizing ATN status. Deep learning techniq...
PET/MRI integrates anatomical, functional and metabolic information, and is increasingly used in the field of clinical oncology, including early diagnosis of disease, local staging, detection of systemic metastases, evaluation of treatment efficacy a...
Fast and low-dose reconstructions of medical images are highly desired in clinical routines. We propose a hybrid deep-learning and iterative reconstruction (hybrid DL-IR) framework and apply it for fast magnetic resonance imaging (MRI), fast positron...
Nuclear medicine review. Central & Eastern Europe
Jan 1, 2023
BACKGROUND: This study aims to evaluate the performance of a deep learning enhancement method in PET images reconstructed with a shorter acquisition time, and different reconstruction algorithms. The impact of the enhancement on clinical decisions wa...
No one can deny the significant impact of artificial intelligence (AI) on everyday life, especially in the health sector where it has emerged as a crucial and beneficial tool in Nuclear Medicine (NM) and molecular imaging. The objective of this revie...