AIMC Topic: Magnetic Resonance Imaging

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Artificial Intelligence in Spine and Paraspinal Muscle Analysis.

Advances in experimental medicine and biology
Disorders affecting the neurological and musculoskeletal systems represent international health burdens. A significant impediment to progress with interventional trials is the absence of responsive, objective, and valid outcome measures sensitive to ...

Machine Learning and Radiomics in Gliomas.

Advances in experimental medicine and biology
The integration of machine learning (ML) and radiomics is emerging as a pivotal advancement in glioma research, offering novel insights into the diagnosis, prognosis, and treatment of these complex tumors. Radiomics involves the extraction of a multi...

Meta-transfer Learning for Brain Tumor Segmentation: Within and Beyond Glioma.

Advances in experimental medicine and biology
In recent years, numerous algorithms have emerged for the segmentation of brain tumors, propelled by both the advancements of deep learning techniques and the influential open benchmark set by the BraTS challenge. This chapter provides an overview of...

Segmentation Synergy with a Dual U-Net and Federated Learning with CNNRF Models for Enhanced Brain Tumor Analysis.

Current medical imaging
BACKGROUND: Brain tumours represent a diagnostic challenge, especially in the imaging area, where the differentiation of normal and pathologic tissues should be precise. The use of up-to-date machine learning techniques would be of great help in term...

Highly accurate brain tumor detection with high sensitivity using transform-based functions and machine learning algorithms.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: Brain tumor is an extremely dangerous disease with a very high mortality rate worldwide. Detecting brain tumors accurately is crucial due to the varying appearance of tumor cells and the dimensional irregularities in their growth. This po...

Fine grained automatic left ventricle segmentation via ROI based Tri-Convolutional neural networks.

Technology and health care : official journal of the European Society for Engineering and Medicine
BACKGROUND: The left ventricle segmentation (LVS) is crucial to the assessment of cardiac function. Globally, cardiovascular disease accounts for the majority of deaths, posing a significant health threat. In recent years, LVS has gained important at...

[Advances in artificial intelligence-assisted MRI radiomics in the diagnosis and treatment of prostate cancer].

Zhonghua nan ke xue = National journal of andrology
Prostate cancer (PCa) is the second most common cancer worldwide and the fifth leading cause of cancer deaths in men. Magnetic resonance imaging (MRI), with its high sensitivity and specificity in detecting PCa, is currently the most widely used imag...

Association between Resting Heart Rate and Machine Learning-Based Brain Age in Middle- and Older-Age.

The journal of prevention of Alzheimer's disease
BACKGROUND: Resting heart rate (RHR), has been related to increased risk of dementia, but the relationship between RHR and brain age is unclear.

Alzheimer's Disease Prediction Using Fly-Optimized Densely Connected Convolution Neural Networks Based on MRI Images.

The journal of prevention of Alzheimer's disease
Alzheimer's is a degenerative brain cell disease that affects around 5.8 million people globally. The progressive neurodegenerative disease known as Alzheimer's Disease (AD), affects the frontal cortex, the part of the brain in charge of memory, lang...