AIMC Topic: Magnetic Resonance Imaging

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Brain tumor segmentation and classification using MRI: Modified segnet model and hybrid deep learning architecture with improved texture features.

Computational biology and chemistry
Brain tumors are quickly overtaking all other causes of death worldwide. The failure to perform a timely diagnosis is the main cause of increasing the death rate. Traditional methods of brain tumor diagnosis heavily rely on the expertise of radiologi...

Applications of artificial intelligence and advanced imaging in pediatric diffuse midline glioma.

Neuro-oncology
Diffuse midline glioma (DMG) is a rare, aggressive, and fatal tumor that largely occurs in the pediatric population. To improve outcomes, it is important to characterize DMGs, which can be performed via magnetic resonance imaging (MRI) assessment. Re...

Role of Brain Age Gap as a Mediator in the Relationship Between Cognitive Impairment Risk Factors and Cognition.

Neurology
BACKGROUND AND OBJECTIVES: Cerebrovascular disease (CeVD) and cognitive impairment risk factors contribute to cognitive decline, but the role of brain age gap (BAG) in mediating this relationship remains unclear, especially in Southeast Asian populat...

Deep learning-based contour propagation in magnetic resonance imaging-guided radiotherapy of lung cancer patients.

Physics in medicine and biology
Fast and accurate organ-at-risk (OAR) and gross tumor volume (GTV) contour propagation methods are needed to improve the efficiency of magnetic resonance (MR) imaging-guided radiotherapy. We trained deformable image registration networks to accuratel...

Predicting depression in healthy young adults: A machine learning approach using longitudinal neuroimaging data.

NeuroImage
Accurate prediction of depressive symptoms in healthy individuals can enable early intervention and reduce both individual and societal costs. This study aimed to develop predictive models for depression in young adults using machine learning (ML) te...

DCSLK: Combined large kernel shared convolutional model with dynamic channel Sampling.

NeuroImage
This study centers around the competition between Convolutional Neural Networks (CNNs) with large convolutional kernels and Vision Transformers in the domain of computer vision, delving deeply into the issues pertaining to parameters and computationa...

A robust automated segmentation method for white matter hyperintensity of vascular-origin.

NeuroImage
White matter hyperintensity (WMH) is a primary manifestation of small vessel disease (SVD), leading to vascular cognitive impairment and other disorders. Accurate WMH quantification is vital for diagnosis and prognosis, but current automatic segmenta...

Real-Time Dose-Guided Radiation Therapy.

International journal of radiation oncology, biology, physics
Dramatic strides have been made in real-time adaptive radiation therapy, where treating single tumors as dynamic but rigid bodies has demonstrated a halving of toxicities for prostate cancer. However, the human body is much more complex than a rigid ...

Contrast-enhanced image synthesis using latent diffusion model for precise online tumor delineation in MRI-guided adaptive radiotherapy for brain metastases.

Physics in medicine and biology
Magnetic resonance imaging-guided adaptive radiotherapy (MRIgART) is a promising technique for long-course radiotherapy of large-volume brain metastasis (BM), due to the capacity to track tumor changes throughout treatment course. Contrast-enhanced T...

Differential dementia detection from multimodal brain images in a real-world dataset.

Alzheimer's & dementia : the journal of the Alzheimer's Association
INTRODUCTION: Artificial intelligence (AI) models have been applied to differential dementia detection tasks in brain images from curated, high-quality benchmark databases, but not real-world data in hospitals.