AIMC Topic: Tomography, Emission-Computed, Single-Photon
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Comparison of post reconstruction- and reconstruction-based deep learning denoising methods in cardiac SPECT.
Biomedical physics & engineering express
Sep 13, 2023
. The quality of myocardial perfusion SPECT (MPS) images is often hampered by low count statistics. Poor image quality might hinder reporting the studies and in the worst case lead to erroneous diagnosis. Deep learning (DL)-based methods can be used ...
Respiratory signal estimation for cardiac perfusion SPECT using deep learning.
Medical physics
Jul 31, 2023
BACKGROUND: Respiratory motion induces artifacts in reconstructed cardiac perfusion SPECT images. Correction for respiratory motion often relies on a respiratory signal describing the heart displacements during breathing. However, using external trac...
Deep learning enhanced ultra-fast SPECT/CT bone scan in patients with suspected malignancy: quantitative assessment and clinical performance.
Physics in medicine and biology
Jun 30, 2023
. To evaluate the clinical performance of deep learning-enhanced ultrafast single photon emission computed tomography/computed tomography (SPECT/CT) bone scans in patients with suspected malignancy.. In this prospective study, 102 patients with poten...
Reduction of SPECT acquisition time using deep learning: A phantom study.
Physica medica : PM : an international journal devoted to the applications of physics to medicine and biology : official journal of the Italian Association of Biomedical Physics (AIFB)
Jun 9, 2023
Single photon emission computed tomography (SPECT) procedures are characterized by long acquisition time to acquire diagnostically acceptable image data. The goal of this investigation was to assess the feasibility of using a deep convolutional neura...
Observer studies of image quality of denoising reduced-count cardiac single photon emission computed tomography myocardial perfusion imaging by three-dimensional Gaussian post-reconstruction filtering and deep learning.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
May 23, 2023
BACKGROUND: The aim of this research was to asses perfusion-defect detection-accuracy by human observers as a function of reduced-counts for 3D Gaussian post-reconstruction filtering vs deep learning (DL) denoising to determine if there was improved ...
Deep learning regressor model based on nigrosome MRI in Parkinson syndrome effectively predicts striatal dopamine transporter-SPECT uptake.
Neuroradiology
May 20, 2023
PURPOSE: Nigrosome imaging using susceptibility-weighted imaging (SWI) and dopamine transporter imaging using I-2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl)-nortropane (I-FP-CIT) single-photon emission computerized tomography (SPECT) can eval...
Differentiation between normal and abnormal kidneys using Tc-DMSA SPECT with deep learning in paediatric patients.
Clinical radiology
May 13, 2023
AIM: To investigate the feasibility of using deep learning (DL) to differentiate normal from abnormal (or scarred) kidneys using technetium-99m dimercaptosuccinic acid (Tc-DMSA) single-photon-emission computed tomography (SPECT) in paediatric patient...
Application of an artificial intelligence ensemble for detection of important secondary findings on lung ventilation and perfusion SPECT-CT.
Clinical imaging
May 2, 2023
RATIONALE: Single-photon-emission-computerized-tomography/computed-tomography(SPECT/CT) is commonly used for pulmonary disease. Scant work has been done to determine ability of AI for secondary findings using low-dose-CT(LDCT) attenuation correction ...
Deep learning to automate SPECT MPI myocardial reorientation.
Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology
Apr 26, 2023
A new method incorporating deep learning with shape priors for left ventricular segmentation in myocardial perfusion SPECT images.
Computers in biology and medicine
Apr 24, 2023
Accurate segmentation of the left ventricle (LV) is crucial for evaluating myocardial perfusion SPECT (MPS) and assessing LV functions. In this study, a novel method combining deep learning with shape priors was developed and validated to extract the...
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