AIMC Topic:
Magnetic Resonance Imaging
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Deep Learning for Perfusion Cerebral Blood Flow (CBF) and Volume (CBV) Predictions and Diagnostics.
Annals of biomedical engineering
Feb 24, 2024
Dynamic susceptibility contrast magnetic resonance perfusion (DSC-MRP) is a non-invasive imaging technique for hemodynamic measurements. Various perfusion parameters, such as cerebral blood volume (CBV) and cerebral blood flow (CBF), can be derived f...
Deep Learning Radiomic Analysis of MRI Combined with Clinical Characteristics Diagnoses Placenta Accreta Spectrum and its Subtypes.
Journal of magnetic resonance imaging : JMRI
Feb 23, 2024
BACKGROUND: Different placenta accreta spectrum (PAS) subtypes pose varying surgical risks to the parturient. Machine learning model has the potential to diagnose PAS disorder.
Artificial intelligence support in MR imaging of incidental renal masses: an early health technology assessment.
European radiology
Feb 23, 2024
OBJECTIVE: This study analyzes the potential cost-effectiveness of integrating an artificial intelligence (AI)-assisted system into the differentiation of incidental renal lesions as benign or malignant on MR images during follow-up.
Development and Preliminary Validation of a Novel Convolutional Neural Network Model for Predicting Treatment Response in Patients with Unresectable Hepatocellular Carcinoma Receiving Hepatic Arterial Infusion Chemotherapy.
Journal of imaging informatics in medicine
Feb 23, 2024
The goal of this study was to evaluate the performance of a convolutional neural network (CNN) with preoperative MRI and clinical factors in predicting the treatment response of unresectable hepatocellular carcinoma (HCC) patients receiving hepatic a...
Mode combinability: Exploring convex combinations of permutation aligned models.
Neural networks : the official journal of the International Neural Network Society
Feb 23, 2024
We explore element-wise convex combinations of two permutation-aligned neural network parameter vectors Θ and Θ of size d. We conduct extensive experiments by examining various distributions of such model combinations parametrized by elements of the ...
Artificial intelligence applied to magnetic resonance imaging reliably detects the presence, but not the location, of meniscus tears: a systematic review and meta-analysis.
European radiology
Feb 22, 2024
OBJECTIVES: To review and compare the accuracy of convolutional neural networks (CNN) for the diagnosis of meniscal tears in the current literature and analyze the decision-making processes utilized by these CNN algorithms.
Improved 3D DESS MR neurography of the lumbosacral plexus with deep learning and geometric image combination reconstruction.
Skeletal radiology
Feb 22, 2024
OBJECTIVE: To evaluate the impact of deep learning (DL) reconstruction in enhancing image quality and nerve conspicuity in LSP MRN using DESS sequences. Additionally, a geometric image combination (GIC) method to improve DESS signals' combination was...
Stop moving: MR motion correction as an opportunity for artificial intelligence.
Magma (New York, N.Y.)
Feb 22, 2024
Subject motion is a long-standing problem of magnetic resonance imaging (MRI), which can seriously deteriorate the image quality. Various prospective and retrospective methods have been proposed for MRI motion correction, among which deep learning ap...
Deep learning model for the detection of prostate cancer and classification of clinically significant disease using multiparametric MRI in comparison to PI-RADs score.
Urologic oncology
Feb 22, 2024
BACKGROUND: The Prostate Imaging Reporting and Data System (PI-RADS) is an established reporting scheme for multiparametric magnetic resonance imaging (mpMRI) to distinguish clinically significant prostate cancer (csPCa). Deep learning (DL) holds gre...
Deep learning-based, fully automated, pediatric brain segmentation.
Scientific reports
Feb 22, 2024
The purpose of this study was to demonstrate the performance of a fully automated, deep learning-based brain segmentation (DLS) method in healthy controls and in patients with neurodevelopmental disorders, SCN1A mutation, under eleven. The whole, cor...
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