Machine learning and deep learning applications in magnetic particle imaging
In recent years, magnetic particle imaging (MPI) has emerged as a promising imaging
technique depicting high sensitivity and spatial resolution. It originated in the early 2000s …
technique depicting high sensitivity and spatial resolution. It originated in the early 2000s …
Artificial intelligence in nuclear cardiology: an update and future trends
Myocardial perfusion imaging (MPI), using either single photon emission computed
tomography (SPECT) or positron emission tomography (PET), is one of the most commonly …
tomography (SPECT) or positron emission tomography (PET), is one of the most commonly …
Machine learning-based diagnosis and risk classification of coronary artery disease using myocardial perfusion imaging SPECT: A radiomics study
This study aimed to investigate the diagnostic performance of machine learning-based
radiomics analysis to diagnose coronary artery disease status and risk from rest/stress …
radiomics analysis to diagnose coronary artery disease status and risk from rest/stress …
Time-to-event overall survival prediction in glioblastoma multiforme patients using magnetic resonance imaging radiomics
Abstract Purpose Glioblastoma Multiforme (GBM) represents the predominant aggressive
primary tumor of the brain with short overall survival (OS) time. We aim to assess the …
primary tumor of the brain with short overall survival (OS) time. We aim to assess the …
Artificial intelligence empowered nuclear medicine and molecular imaging in cardiology: a state-of-the-art review
J Li, G Yang, L Zhang - Phenomics, 2023 - Springer
Nuclear medicine and molecular imaging plays a significant role in the detection and
management of cardiovascular disease (CVD). With recent advancements in computer …
management of cardiovascular disease (CVD). With recent advancements in computer …
Dual-centre harmonised multimodal positron emission tomography/computed tomography image radiomic features and machine learning algorithms for non-small cell …
Aims We aimed to build radiomic models for classifying non-small cell lung cancer (NSCLC)
histopathological subtypes through a dual-centre dataset and comprehensively evaluate the …
histopathological subtypes through a dual-centre dataset and comprehensively evaluate the …
Comparing various AI approaches to traditional quantitative assessment of the myocardial perfusion in [82Rb] PET for MACE prediction
Assessing the individual risk of Major Adverse Cardiac Events (MACE) is of major
importance as cardiovascular diseases remain the leading cause of death worldwide …
importance as cardiovascular diseases remain the leading cause of death worldwide …
Machine learning based on SPECT/CT to differentiate bone metastasis and benign bone lesions in lung malignancy patients
H Wang, Y Chen, J Qiu, J **e, W Lu, J Ma… - Medical …, 2024 - Wiley Online Library
Background Bone metastasis is a common event in lung cancer progression. Early
diagnosis of lung malignant tumor with bone metastasis is crucial for selecting effective …
diagnosis of lung malignant tumor with bone metastasis is crucial for selecting effective …
Left Ventricular Myocardial Dysfunction Evaluation in Thalassemia Patients Using Echocardiographic Radiomic Features and Machine Learning Algorithms
Heart failure caused by iron deposits in the myocardium is the primary cause of mortality in
beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the …
beta-thalassemia major patients. Cardiac magnetic resonance imaging (CMRI) T2* is the …
Current status and future directions in artificial intelligence for nuclear cardiology
Introduction Myocardial perfusion imaging (MPI) is one of the most commonly ordered
cardiac imaging tests. Accurate motion correction, image registration, and reconstruction are …
cardiac imaging tests. Accurate motion correction, image registration, and reconstruction are …