AI model predicts neural network degeneration patterns in ALS progression

New research from the University of St Andrews, the University of Copenhagen and Drexel University has developed AI ...

3D hybrid imaging system could address limitations of MRI, CT and ultrasound

In a proof-of-concept study, researchers from the Keck School of Medicine of USC and the California Institute of Technology ...
IEEE

DIMA: DIffusing Motion Artifacts for Unsupervised Correction in Brain MRI Images

Abstract: Motion artifacts remain a significant challenge in Magnetic Resonance Imaging (MRI), compromising diagnostic quality and potentially leading to misdiagnoses or repeated scans. Existing deep ...
IEEE

Hybrid CNN-Based Transfer Learning Enhances Brain Tumor Classification on MRI Images

Abstract: Brain tumors are among the deadliest diseases worldwide and require early and accurate diagnosis via Magnetic Resonance Imaging (MRI). Deep learning techniques, particularly convolutional ...
Frontiers

Deep learning-driven MRI for accurate brain volumetry in murine models of neurodegenerative diseases

1 Novartis Biomedical Research, Basel, Switzerland 2 École Polytechnique Fédérale de Lausanne, School of Engineering, Lausanne, Switzerland In vivo experimental procedures adhered to Swiss animal ...
Fox News

New MRI brain scan predicts Alzheimer's risk years before symptoms develop

Levels of iron in the brain could be a warning sign of future Alzheimer’s disease, a new study suggests. High levels of the chemical element have been shown to increase brain toxins and trigger ...
Scientific Research Publishing

From U-Net to Swin-Unet Transformers: The Next-Generation Advances in Brain Tumor Segmentation with Deep Learning ()

Brain tumor segmentation is a vital step in diagnosis, treatment planning, and prognosis in neuro-oncology. In recent years, deep learning approaches have revolutionized this field, evolving from the ...
Frontiers

A nnU-Net-based automatic segmentation of FCD type II lesions in 3D FLAIR MRI images

Focal cortical dysplasia (FCD) type II is a common cause of epilepsy and is challenging to detect due to its similarities with other brain conditions. Finding these lesions accurately is essential for ...