AIMC Topic: Positron-Emission Tomography
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A Scoping Review of Machine-Learning Derived Radiomic Analysis of CT and PET Imaging to Investigate Atherosclerotic Cardiovascular Disease.
Tomography (Ann Arbor, Mich.)
Sep 3, 2024
BACKGROUND: Cardiovascular disease affects the carotid arteries, coronary arteries, aorta and the peripheral arteries. Radiomics involves the extraction of quantitative data from imaging features that are imperceptible to the eye. Radiomics analysis ...
Advancing Tau PET Quantification in Alzheimer Disease with Machine Learning: Introducing THETA, a Novel Tau Summary Measure.
Journal of nuclear medicine : official publication, Society of Nuclear Medicine
Sep 3, 2024
Alzheimer disease (AD) exhibits spatially heterogeneous 3- or 4-repeat tau deposition across participants. Our overall goal was to develop an automated method to quantify the heterogeneous burden of tau deposition into a single number that would be c...
Deep learning applications for quantitative and qualitative PET in PET/MR: technical and clinical unmet needs.
Magma (New York, N.Y.)
Aug 21, 2024
We aim to provide an overview of technical and clinical unmet needs in deep learning (DL) applications for quantitative and qualitative PET in PET/MR, with a focus on attenuation correction, image enhancement, motion correction, kinetic modeling, and...
Physically informed deep neural networks for metabolite-corrected plasma input function estimation in dynamic PET imaging.
Computer methods and programs in biomedicine
Aug 20, 2024
INTRODUCTION: We propose a novel approach for the non-invasive quantification of dynamic PET imaging data, focusing on the arterial input function (AIF) without the need for invasive arterial cannulation.
An end-to-end deep learning pipeline to derive blood input with partial volume corrections for automated parametric brain PET mapping.
Biomedical physics & engineering express
Aug 19, 2024
Dynamic 2-[18F] fluoro-2-deoxy-D-glucose positron emission tomography (dFDG-PET) for human brain imaging has considerable clinical potential, yet its utilization remains limited. A key challenge in the quantitative analysis of dFDG-PET is characteriz...
Self-normalization for a 1 mmresolution clinical PET system using deep learning.
Physics in medicine and biology
Aug 14, 2024
This work proposes, for the first time, an image-based end-to-end self-normalization framework for positron emission tomography (PET) using conditional generative adversarial networks (cGANs).We evaluated different approaches by exploring each of the...
Big Data Analytics on Lung Cancer Diagnosis Framework With Deep Learning.
IEEE/ACM transactions on computational biology and bioinformatics
Aug 8, 2024
As the segment of diseased tissue in PET images is time-consuming, laborious and low accuracy, this work proposes an automated framework for PET image screening, denoising and diseased tissue segmentation. First, taking into account the characteristi...
The impact of multicentric datasets for the automated tumor delineation in primary prostate cancer using convolutional neural networks on F-PSMA-1007 PET.
Radiation oncology (London, England)
Aug 7, 2024
PURPOSE: Convolutional Neural Networks (CNNs) have emerged as transformative tools in the field of radiation oncology, significantly advancing the precision of contouring practices. However, the adaptability of these algorithms across diverse scanner...
Two-step optimization for accelerating deep image prior-based PET image reconstruction.
Radiological physics and technology
Aug 3, 2024
Deep learning, particularly convolutional neural networks (CNNs), has advanced positron emission tomography (PET) image reconstruction. However, it requires extensive, high-quality training datasets. Unsupervised learning methods, such as deep image ...
Gated SPECT-Derived Myocardial Strain Estimated From Deep-Learning Image Translation Validated From N-13 Ammonia PET.
Academic radiology
Aug 2, 2024
RATIONALE AND OBJECTIVES: This study investigated the use of deep learning-generated virtual positron emission tomography (PET)-like gated single-photon emission tomography (SPECT) for assessing myocardial strain, overcoming limitations of convention...
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