AIMC Topic: Magnetic Resonance Imaging
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T2-weighted imaging of rectal cancer using a 3D fast spin echo sequence with and without deep learning reconstruction: A reader study.
Journal of applied clinical medical physics
Feb 20, 2025
PURPOSE: To compare image quality and clinical utility of a T2-weighted (T2W) 3-dimensional (3D) fast spin echo (FSE) sequence using deep learning reconstruction (DLR) versus conventional reconstruction for rectal magnetic resonance imaging (MRI).
Artificial intelligence and different image modalities in uveal melanoma diagnosis and prognosis: A narrative review.
Photodiagnosis and photodynamic therapy
Feb 20, 2025
BACKGROUND: The most widespread primary intraocular tumor in adults is called uveal melanoma (UM), if detected early enough, it can be curable. Various methods are available to treat UM, but the most commonly used and effective approach is plaque rad...
Assessment of breast composition in MRI using artificial intelligence - A systematic review.
Radiography (London, England : 1995)
Feb 20, 2025
INTRODUCTION: Magnetic Resonance Imaging (MRI) performs a critical role in breast cancer diagnosis, especially for high-risk populations e.g. family history. MRI could take advantage of the implementation of artificial intelligence (AI). AI assessmen...
Development of a Machine-Learning Algorithm to Identify Cauda Equina Compression on Magnetic Resonance Imaging Scans.
World neurosurgery
Feb 20, 2025
OBJECTIVE: Cauda equina syndrome (CES) poses significant neurological risks if untreated. Diagnosis relies on clinical and radiological features. As the symptoms are often nonspecific and common, the diagnosis is usually made after a magnetic resonan...
Robust Myocardial Perfusion MRI Quantification With DeepFermi.
IEEE transactions on bio-medical engineering
Feb 20, 2025
Stress perfusion cardiac magnetic resonance is an important technique for examining and assessing the blood supply of the myocardium. Currently, the majority of clinical perfusion scans are evaluated based on visual assessment by experienced clinicia...
Learning-based inference of longitudinal image changes: Applications in embryo development, wound healing, and aging brain.
Proceedings of the National Academy of Sciences of the United States of America
Feb 20, 2025
Longitudinal imaging data are routinely acquired for health studies and patient monitoring. A central goal in longitudinal studies is tracking relevant change over time. Traditional methods remove nuisance variation with custom pipelines to focus on ...
IConDiffNet: an unsupervised inverse-consistent diffeomorphic network for medical image registration.
Physics in medicine and biology
Feb 20, 2025
Deformable image registration (DIR) is critical in many medical imaging applications. Diffeomorphic transformations, which are smooth invertible mappings with smooth inverses preserve topological properties and are an anatomically plausible means of ...
A novel generative model for brain tumor detection using magnetic resonance imaging.
Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society
Feb 19, 2025
Brain tumors are a disease that kills thousands of people worldwide each year. Early identification through diagnosis is essential for monitoring and treating patients. The proposed study brings a new method through intelligent computational cells th...
Multimodal deep learning fusion of ultrafast-DCE MRI and clinical information for breast lesion classification.
Computers in biology and medicine
Feb 19, 2025
BACKGROUND: Breast cancer is the most common cancer worldwide, and magnetic resonance imaging (MRI) constitutes a very sensitive technique for invasive cancer detection. When reviewing breast MRI examination, clinical radiologists rely on multimodal ...
Integrative diagnosis of psychiatric conditions using ChatGPT and fMRI data.
BMC psychiatry
Feb 19, 2025
BACKGROUND: Traditional diagnostic methods for psychiatric disorders often rely on subjective assessments, leading to inconsistent diagnoses. Integrating advanced natural language processing (NLP) techniques with neuroimaging data may improve diagnos...
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