Neuroimaging clinics of North America
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Neuroimaging Clin. N. Am. · Aug 2020
ReviewArtificial Intelligence in Head and Neck Imaging: A Glimpse into the Future.
Artificial intelligence, specifically machine learning and deep learning, is a rapidly developing field in imaging sciences with the potential to improve the efficiency and effectiveness of radiologists. This review covers common technical terms and basic concepts in imaging artificial intelligence and briefly reviews the application of these techniques to general imaging as well as head and neck imaging. Artificial intelligence has the potential to contribute improvements to all areas of patient care, including image acquisition, processing, segmentation, automated detection of findings, integration of clinical information, quality improvement, and research. Numerous challenges remain, however, before widespread imaging clinical adoption and integration occur.
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Neuroimaging Clin. N. Am. · May 2020
ReviewMagnetoencephalography Research in Pediatric Autism Spectrum Disorder.
Magnetoencephalography (MEG) research indicates differences in neural brain measures in children with autism spectrum disorder (ASD) compared to typically developing (TD) children. As reviewed here, resting-state MEG exams are of interest as well as MEG paradigms that assess neural function across domains (e.g., auditory, resting state). To date, MEG research has primarily focused on group-level differences. Research is needed to explore whether MEG measures can predict, at the individual level, ASD diagnosis, prognosis (future severity), and response to therapy.
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This article provides an overview of research that uses magnetoencephalography to understand the brain basis of human language. The cognitive processes and brain networks that have been implicated in written and spoken language comprehension and production are discussed in relation to different methodologies: we review event-related brain responses, research on the coupling of neural oscillations to speech, oscillatory coupling between brain regions (eg, auditory-motor coupling), and neural decoding approaches in naturalistic language comprehension.