EEG signal processing for biomedical applications
Focuses on electroencephalography (EEG) signal processing in biomedical engineering applications. EEG signals are used widely in clinical and research settings to provide cognitive and emotional state information. In addition to capturing complex neural patterns at high speeds, EEG signals are a reliable and non-invasive way of measuring the electrical activity in the brain. By examining various novel analysis and signal processing methods, this collection of papers provides a better understanding of cognitive states and brain activity.
Brainlesion: Glioma, Multiple Sclerosis, Stroke and Traumatic Brain Injuries ; 7th International Workshop, BrainLes 2021, Held in Conjunction with MICCAI 2021, Virtual Event, September 27, 2021, Revised Selected Papers, Part I
The content of thebook covers the current state-of-the-art literature on federated learning applications for cancer research and Vclinical oncology analysis, as well as an overview of the deep learning approaches improving the current standard of care for brain lesions and current neuroimaging challenges. It is also focusing on the accepted BrainLes workshop submissions, is to provide an overview of new advances of medical image analysis in all the aforementioned brain pathologies. It brings together researchers from the medical image analysis domain, neurologists, and radiologists working on at least one of these diseases. The aim is to consider neuroimaging biomarkers used for one disease applied to the other diseases.

