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Magnetic Resonance Imaging

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Anatomy-derived 3D Aortic Hemodynamics Using Fluid Physics-informed Deep Learning.

Radiology
Background Four-dimensional (4D) flow MRI provides assessment of thoracic aorta hemodynamic measures that are increasingly recognized as important biomarkers for risk assessment. However, long acquisition times and cumbersome data analysis limit wide...

brain2print AI powered web tool for creating 3D printable brain models.

Scientific reports
We introduce brain2print, a web-based application that converts T1-weighted MRI scans into 3D printable models. By leveraging artificial intelligence (AI), brain2print performs all computations directly on the user's device, preserving privacy while ...

Feasibility of virtual T2-weighted fat-saturated breast MRI images by convolutional neural networks.

European radiology experimental
BACKGROUND: Breast magnetic resonance imaging (MRI) protocols often include T2-weighted fat-saturated (T2w-FS) sequences, which support tissue characterization but significantly increase scan time. This study aims to evaluate whether a 2D-U-Net neura...

Evaluating prostate cancer diagnostic methods: The role and relevance of digital rectal examination in modern era.

Investigative and clinical urology
This review examines diagnostic methods for prostate cancer, focusing on the role of digital rectal examination (DRE) alongside modern advancements like prostate-specific antigen (PSA) testing, Prostate Health Index (PHI), magnetic resonance imaging ...

Development and validation of machine learning algorithms for early detection of ankylosing spondylitis using magnetic resonance images.

Technology and health care : official journal of the European Society for Engineering and Medicine
BackgroundAnkylosing spondylitis (AS) is a chronic inflammatory disease affecting the sacroiliac joints and spine, often leading to disability if not diagnosed and treated early.ObjectiveIn this study, we present the development and validation of mac...

Brain multi modality image inpainting via deep learning based edge region generative adversarial network.

Technology and health care : official journal of the European Society for Engineering and Medicine
A brain tumor (BT) is considered one of the most crucial and deadly diseases in the world, as it affects the central nervous system and its main functions. Headaches, nausea, and balance problems are caused by tumors pressing on nearby brain tissue a...

OA-HybridCNN (OHC): An advanced deep learning fusion model for enhanced diagnostic accuracy in knee osteoarthritis imaging.

PloS one
Knee osteoarthritis (KOA) is a leading cause of disability globally. Early and accurate diagnosis is paramount in preventing its progression and improving patients' quality of life. However, the inconsistency in radiologists' expertise and the onset ...

Semisupervised adaptive learning models for IDH1 mutation status prediction.

PloS one
The mutation status of isocitrate dehydrogenase1 (IDH1) in glioma is critical information for the diagnosis, treatment, and prognosis. Accurately determining such information from MRI data has emerged as a significant research challenge in recent yea...

Artifact estimation network for MR images: effectiveness of batch normalization and dropout layers.

BMC medical imaging
BACKGROUND: Magnetic resonance imaging (MRI) is an essential tool for medical diagnosis. However, artifacts may degrade images obtained through MRI, especially owing to patient movement. Existing methods that mitigate the artifact problem are subject...