AIMC Topic: Positron-Emission Tomography
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The Value of Artificial Intelligence in Prostate-Specific Membrane Antigen Positron Emission Tomography: An Update.
Seminars in nuclear medicine
Jan 31, 2025
This review aims to provide an up-to-date overview of the utility of artificial intelligence (AI) in evaluating prostate-specific membrane antigen (PSMA) positron emission tomography (PET) scans for prostate cancer (PCa). A literature review was cond...
Self-supervised parametric map estimation for multiplexed PET with a deep image prior.
Physics in medicine and biology
Jan 31, 2025
Multiplexed positron emission tomography (mPET) imaging allows simultaneous observation of physiological and pathological information from multiple tracers in a single PET scan. Although supervised deep learning has demonstrated superior performance ...
Continuous single-ended depth-of-interaction measurement using highly multiplexed signals and artificial neural networks.
Physics in medicine and biology
Jan 27, 2025
. This study aims to enhance positron emission tomography (PET) imaging systems by developing a continuous depth-of-interaction (DOI) measurement technique using a single-ended readout. Our primary focus is on reducing the number of readout channels ...
Non-parametric Bayesian deep learning approach for whole-body low-dose PET reconstruction and uncertainty assessment.
Medical & biological engineering & computing
Jan 23, 2025
Positron emission tomography (PET) imaging plays a pivotal role in oncology for the early detection of metastatic tumors and response to therapy assessment due to its high sensitivity compared to anatomical imaging modalities. The balance between ima...
Empowering PET imaging reporting with retrieval-augmented large language models and reading reports database: a pilot single center study.
European journal of nuclear medicine and molecular imaging
Jan 23, 2025
PURPOSE: The potential of Large Language Models (LLMs) in enhancing a variety of natural language tasks in clinical fields includes medical imaging reporting. This pilot study examines the efficacy of a retrieval-augmented generation (RAG) LLM system...
Modernizing Neuro-Oncology: The Impact of Imaging, Liquid Biopsies, and AI on Diagnosis and Treatment.
International journal of molecular sciences
Jan 22, 2025
Advances in neuro-oncology have transformed the diagnosis and management of brain tumors, which are among the most challenging malignancies due to their high mortality rates and complex neurological effects. Despite advancements in surgery and chemor...
Machine learning models for dementia screening to classify brain amyloid positivity on positron emission tomography using blood markers and demographic characteristics: a retrospective observational study.
Alzheimer's research & therapy
Jan 21, 2025
BACKGROUND: Intracerebral amyloid β (Aβ) accumulation is considered the initial observable event in the pathological process of Alzheimer's disease (AD). Efficient screening for amyloid pathology is critical for identifying patients for early treatme...
Clinical impact of an explainable machine learning with amino acid PET imaging: application to the diagnosis of aggressive glioma.
European journal of nuclear medicine and molecular imaging
Jan 17, 2025
PURPOSE: Radiomics-based machine learning (ML) models of amino acid positron emission tomography (PET) images have shown efficiency in glioma prediction tasks. However, their clinical impact on physician interpretation remains limited. This study inv...
Clinical validation of artificial intelligence-based single-subject morphometry without normative reference database.
Journal of Alzheimer's disease : JAD
Jan 12, 2025
BACKGROUND: Single-subject voxel-based morphometry (VBM) is a powerful technique for reader-independent detection of brain atrophy in structural magnetic resonance imaging (MRI) to support the (differential) diagnosis and staging of neurodegenerative...
Explainable PET-Based Habitat and Peritumoral Machine Learning Model for Predicting Progression-free Survival in Clinical Stage IA Pure-Solid Non-small Cell Lung Cancer: A Two-center Study.
Academic radiology
Jan 4, 2025
RATIONALE AND OBJECTIVES: This study aimed to develop and validate machine learning (ML) models utilizing positron emission tomography (PET)-habitat of the tumor and its peritumoral microenvironment to predict progression-free survival (PFS) in patie...
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