AIMC Topic: Perfusion
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A deep learning approach for quantifying CT perfusion parameters in stroke.
Biomedical physics & engineering express
Apr 16, 2025
. Computed tomography perfusion (CTP) imaging is widely used for assessing acute ischemic stroke. However, conventional methods for quantifying CTP images, such as singular value decomposition (SVD), often lead to oscillations in the estimated residu...
Machine Learning Algorithms in Controlled Donation After Circulatory Death Under Normothermic Regional Perfusion: A Graft Survival Prediction Model.
Transplantation
Jan 9, 2025
BACKGROUND: Several scores have been developed to stratify the risk of graft loss in controlled donation after circulatory death (cDCD). However, their performance is unsatisfactory in the Spanish population, where most cDCD livers are recovered usin...
Identification and validation of biomarkers related to mitochondria during ex vivo lung perfusion for lung transplants based on machine learning algorithm.
Gene
Nov 15, 2024
BACKGROUND: Ex vivo lung perfusion (EVLP) is a critical strategy to rehabilitate marginal donor lungs, thereby increasing lung transplantation (LTx) rates. Ischemia-reperfusion (I/R) injury inevitably occurs during LTx. Exploring the common mechanism...
An accessible deep learning tool for voxel-wise classification of brain malignancies from perfusion MRI.
Cell reports. Medicine
Mar 11, 2024
Noninvasive differential diagnosis of brain tumors is currently based on the assessment of magnetic resonance imaging (MRI) coupled with dynamic susceptibility contrast (DSC). However, a definitive diagnosis often requires neurosurgical interventions...
Clinical Feasibility of Deep Learning-Based Attenuation Correction Models for Tl-201 Myocardial Perfusion SPECT.
Clinical nuclear medicine
Feb 26, 2024
PURPOSE: We aimed to develop deep learning (DL)-based attenuation correction models for Tl-201 myocardial perfusion SPECT (MPS) images and evaluate their clinical feasibility.
Increased brain fractional perfusion in obesity using intravoxel incoherent motion (IVIM) MRI metrics.
Obesity (Silver Spring, Md.)
Feb 21, 2024
OBJECTIVE: This research seeks to shed light on the associations between brain perfusion, cognitive function, and mental health in individuals with and without obesity.
A deep learning image analysis method for renal perfusion estimation in pseudo-continuous arterial spin labelling MRI.
Magnetic resonance imaging
Sep 28, 2023
Accurate segmentation of renal tissues is an essential step for renal perfusion estimation and postoperative assessment of the allograft. Images are usually manually labeled, which is tedious and prone to human error. We present an image analysis met...
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...
Automatic Myocardial Contrast Echocardiography Image Quality Assessment Using Deep Learning: Impact on Myocardial Perfusion Evaluation.
Ultrasound in medicine & biology
Jul 24, 2023
OBJECTIVE: The image quality of myocardial contrast echocardiography (MCE) is critical for precise myocardial perfusion evaluation but challenging for echocardiographers. Differences in quality may lead to diagnostic heterogeneity. This study was aim...
Deep learning-based combination of [18F]-FDG PET and CT images for producing pulmonary perfusion image.
Medical physics
Jun 30, 2023
BACKGROUND: The main application of [18F] FDG-PET ( FDG-PET) and CT images in oncology is tumor identification and quantification. Combining PET and CT images to mine pulmonary perfusion information for functional lung avoidance radiation therapy (FL...
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