AIMC Topic:
Magnetic Resonance Imaging
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Radiomics and artificial intelligence applications in pediatric brain tumors.
World journal of pediatrics : WJP
Jun 27, 2024
BACKGROUND: The study of central nervous system (CNS) tumors is particularly relevant in the pediatric population because of their relatively high frequency in this demographic and the significant impact on disease- and treatment-related morbidity an...
Detection and Segmentation of Glioma Tumors Utilizing a UNet Convolutional Neural Network Approach with Non-Subsampled Shearlet Transform.
Journal of computational biology : a journal of computational molecular cell biology
Jun 27, 2024
The prompt and precise identification and delineation of tumor regions within glioma brain images are critical for mitigating the risks associated with this life-threatening ailment. In this study, we employ the UNet convolutional neural network (CNN...
Artificial intelligence for neuro MRI acquisition: a review.
Magma (New York, N.Y.)
Jun 26, 2024
OBJECT: To review recent advances of artificial intelligence (AI) in enhancing the efficiency and throughput of the MRI acquisition workflow in neuroimaging, including planning, sequence design, and correction of acquisition artifacts.
Identifying significant structural factors associated with knee pain severity in patients with osteoarthritis using machine learning.
Scientific reports
Jun 26, 2024
Our main objective was to use machine learning methods to identify significant structural factors associated with pain severity in knee osteoarthritis patients. Additionally, we assessed the potential of various classes of imaging data using machine ...
Individual characteristics outperform resting-state fMRI for the prediction of behavioral phenotypes.
Communications biology
Jun 26, 2024
In this study, we aimed to compare imaging-based features of brain function, measured by resting-state fMRI (rsfMRI), with individual characteristics such as age, gender, and total intracranial volume to predict behavioral measures. We developed a ma...
Multi-grained contrastive representation learning for label-efficient lesion segmentation and onset time classification of acute ischemic stroke.
Medical image analysis
Jun 25, 2024
Ischemic lesion segmentation and the time since stroke (TSS) onset classification from paired multi-modal MRI imaging of unwitnessed acute ischemic stroke (AIS) patients is crucial, which supports tissue plasminogen activator (tPA) thrombolysis decis...
A non-invasive artificial intelligence model for identifying axillary pathological complete response to neoadjuvant chemotherapy in breast cancer: a secondary analysis to multicenter clinical trial.
British journal of cancer
Jun 25, 2024
BACKGROUND: This study aims to develop a stacking model for accurately predicting axillary lymph node (ALN) response to neoadjuvant chemotherapy (NAC) using longitudinal MRI in breast cancer.
Immune Cell-Based Microrobots for Remote Magnetic Actuation, Antitumor Activity, and Medical Imaging.
Advanced healthcare materials
Jun 25, 2024
Translating medical microrobots into clinics requires tracking, localization, and performing assigned medical tasks at target locations, which can only happen when appropriate design, actuation mechanisms, and medical imaging systems are integrated i...
CMRxRecon: A publicly available k-space dataset and benchmark to advance deep learning for cardiac MRI.
Scientific data
Jun 25, 2024
Cardiac magnetic resonance imaging (CMR) has emerged as a valuable diagnostic tool for cardiac diseases. However, a significant drawback of CMR is its slow imaging speed, resulting in low patient throughput and compromised clinical diagnostic quality...
Three autism subtypes based on single-subject gray matter network revealed by semi-supervised machine learning.
Autism research : official journal of the International Society for Autism Research
Jun 24, 2024
Autism spectrum disorder (ASD) is a heterogeneous, early-onset neurodevelopmental condition characterized by persistent impairments in social interaction and communication. This study aims to delineate ASD subtypes based on individual gray matter bra...
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