AIMC Topic: Positron-Emission Tomography
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The Value of Machine Learning-based Radiomics Model Characterized by PET Imaging with Ga-FAPI in Assessing Microvascular Invasion of Hepatocellular Carcinoma.
Academic radiology
Dec 7, 2024
RATIONALE AND OBJECTIVES: This study aimed to develop a radiomics model characterized by Ga-fibroblast activation protein inhibitors (FAPI) positron emission tomography (PET) imaging to predict microvascular invasion (MVI) of hepatocellular carcinoma...
A multi-view learning approach with diffusion model to synthesize FDG PET from MRI T1WI for diagnosis of Alzheimer's disease.
Alzheimer's & dementia : the journal of the Alzheimer's Association
Dec 6, 2024
INTRODUCTION: This study presents a novel multi-view learning approach for machine learning (ML)-based Alzheimer's disease (AD) diagnosis.
Self-supervised neural network for Patlak-based parametric imaging in dynamic [F]FDG total-body PET.
European journal of nuclear medicine and molecular imaging
Dec 2, 2024
PURPOSE: The objective of this study is to generate reliable K parametric images from a shortened [F]FDG total-body PET for clinical applications using a self-supervised neural network algorithm.
3D full-dose brain-PET volume recovery from low-dose data through deep learning: quantitative assessment and clinical evaluation.
European radiology
Nov 28, 2024
OBJECTIVES: Low-dose (LD) PET imaging would lead to reduced image quality and diagnostic efficacy. We propose a deep learning (DL) method to reduce radiotracer dosage for PET studies while maintaining diagnostic quality.
A deep learning method for the recovery of standard-dose imaging quality from ultra-low-dose PET on wavelet domain.
European journal of nuclear medicine and molecular imaging
Nov 25, 2024
PURPOSE: Recent development in positron emission tomography (PET) dramatically increased the effective sensitivity by increasing the geometric coverage leading to total-body PET imaging. This encouraging breakthrough brings the hope of ultra-low dose...
Multi-scale multimodal deep learning framework for Alzheimer's disease diagnosis.
Computers in biology and medicine
Nov 22, 2024
Multimodal neuroimaging data, including magnetic resonance imaging (MRI) and positron emission tomography (PET), provides complementary information about the brain that can aid in Alzheimer's disease (AD) diagnosis. However, most existing deep learni...
Multiclass classification of Alzheimer's disease prodromal stages using sequential feature embeddings and regularized multikernel support vector machine.
NeuroImage
Nov 19, 2024
The detection of patients in the cognitive normal (CN), mild cognitive impairment (MCI), and Alzheimer's disease (AD) stages of neurodegeneration is crucial for early treatment interventions. However, the heterogeneity of MCI data samples poses a cha...
From Images to Genes: Radiogenomics Based on Artificial Intelligence to Achieve Non-Invasive Precision Medicine in Cancer Patients.
Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Nov 13, 2024
With the increasing demand for precision medicine in cancer patients, radiogenomics emerges as a promising frontier. Radiogenomics is originally defined as a methodology for associating gene expression information from high-throughput technologies wi...
Brain imaging and machine learning reveal uncoupled functional network for contextual threat memory in long sepsis.
Scientific reports
Nov 12, 2024
Positron emission tomography (PET) utilizes radiotracers like [F]fluorodeoxyglucose (FDG) to measure brain activity in health and disease. Performing behavioral tasks between the FDG injection and the PET scan allows the FDG signal to reflect task-re...
Using interpretable deep learning radiomics model to diagnose and predict progression of early AD disease spectrum: a preliminary [F]FDG PET study.
European radiology
Oct 31, 2024
OBJECTIVES: In this study, we propose an interpretable deep learning radiomics (IDLR) model based on [F]FDG PET images to diagnose the clinical spectrum of Alzheimer's disease (AD) and predict the progression from mild cognitive impairment (MCI) to A...
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