This resulted in a feature set with a size of 2 x 16 x 255, where: A multi-layer perceptron (MLP) was used to classify these features based on the idea that abnormalities can affect the symmetry of ...

Long-COVID patients with neuropsychiatric symptoms such as brain fog showed abnormal brain activity on magnetic resonance imaging (MRI) while completing memory tests, with a shift from activity in ...

A 64-year-old man from the UK was diagnosed with a brain tumour after doctors initially dismissed his symptoms for ...

so that two types of MRI provide better insights for diagnosis using deep learning and hence avoiding time and efforts. Following is the table for highlight style for different type of elements ...

Brain Abnormalities,Brain MRI Images,Brain Tissue,CNN Classifier,Classification Techniques,Computed Tomography,Computer-aided Diagnosis,Computer-aided Diagnosis System,Convolution ...

The techniques are useful to characterize abnormal brain development due to genetic mutations and structural ... Recently, we have published papers on in vivo diffusion magnetic resonance ...

Main outcome measures Findings on brain MRI, neurocognitive test results and reported fatigue. Results Twenty-five patients (71%) had abnormalities on MRI; multiple white matter lesions were the most ...

Therefore, the aim of the present work was to study brain injuries in preterm infants performing concomitant cUS and MRI at full-term age. Methods In a population-based cohort of 72 extremely low ...

Advanced Machine Learning,Bounding Box,Brain Abnormalities,Brain MRI Images,Brain Tissue,Brain Tumor Detection,Computed Tomography,Convolutional Layers,Deep Learning ...