A team of researchers have developed a deep learning model that is capable of classifying a brain tumor as one of six common types using a single 3D MRI scan, according to a new study.

This is a critical first step in, for example, developing algorithms that can spot brain tumors, or understanding how depression changes brain connectivity.

This AI toolkit uses deep learning algorithms for its segmentation of tumors into four tissue categories consisting of non-tumoral, enhancing proliferative, peritumoral edema, and necrotic.

AI-based evaluation of medical imaging data usually requires a specially developed algorithm for each task. Scientists have now presented a new method for configuring self-learning algorithms for ...

Researchers develop a deep learning framework to accelerate ultra-low-field brain MRI, achieving faster scan times and enhanced image quality. The method shows promise in making MRI more ...

A new AI study describes a machine learning algorithm that was able to classify schizophrenia, based on brain images, with 87 percent accuracy.

The deep-learning technique takes seconds and could give clinicians an accurate idea of brain age while the patient is still in the scanner. The method is a standard deep-learning technique.

Recent research has focused on developing deep-learning-based models to translate low-field 64mT MRI scans to high-field 3T images.