Computer vision and image synthesis technologies are rapidly progressing, presenting prominent applications in various domains, with neurology being a markedly affected field. This revolutionary shift promises more precise, expedient, and reliable techniques for diagnosing, treating, and monitoring neurological disorders, propelling innovations in patient care, augmenting research, and enriching apprehension about brain disorders
The key objective of this Research Topic is to evaluate how Computer Vision and Image synthesis have impacted neurology and its applications, the incorporation of these technologies into neurological investigations, improving prognosis, and more. This Topic also aims to bring forth various image synthesis technologies simulating neurological ailments and potential surgeries, thereby facilitating research and preparing for real-time situations.
We aim to delve into how they fortify medical imaging analysis of MRIs, CT, and X-ray scans, bolstering the detection and diagnosis of neurological afflictions, including brain tumors and strokes. Simultaneously, we'll discuss the role of image synthesis in creating realistic depictions of neurological conditions and potential surgeries, facilitating advancements in research and clinical preparation. With this, we aspire to showcase how these cutting-edge technologies are revolutionizing neurological investigations and improving prognosis, ultimately underscoring their significance in the field.
The scope of this Research Topic covers the amalgamation of computer vision, image synthesis, and neurological perspectives. Specific themes include, but is not limited to:
-Improvements in image processing, analysis, and segmentation techniques for neurological imaging.
-Innovative algorithms and structures for brain lesion identification, quantification, and tracking.
-Applications and effects of deep learning on neurology regarding diagnosis, treatment plans, and prognosis.
-Image synthesis utilities in simulating neurological disorders and surgeries.
-Integration of computer vision and image synthesis in tailored therapy planning and evaluation.
-Ethical, legal, and social implications of employing computer vision and image synthesis in neurology.
Manuscripts dealing with innovative deep learning algorithms for diagnosis, treatment plan, and prognosis of neurological afflictions fall within the scope of Frontiers in Computational Neuroscience. Manuscripts related to improvements in Image processing fall within the scope of the Image Processing section and all the manuscripts mainly dealing with the Neurological applications fall within the scope of the Neurotechnology section.
We welcome various manuscript types including, but not limited to: Review, Original Research, Manuscript Summary, Method, Perspective, Correction, Data Report, Technology and Code, Opinion, Brief Research Report, General Commentary, and Hypothesis and Theory.
Computer vision and image synthesis technologies are rapidly progressing, presenting prominent applications in various domains, with neurology being a markedly affected field. This revolutionary shift promises more precise, expedient, and reliable techniques for diagnosing, treating, and monitoring neurological disorders, propelling innovations in patient care, augmenting research, and enriching apprehension about brain disorders
The key objective of this Research Topic is to evaluate how Computer Vision and Image synthesis have impacted neurology and its applications, the incorporation of these technologies into neurological investigations, improving prognosis, and more. This Topic also aims to bring forth various image synthesis technologies simulating neurological ailments and potential surgeries, thereby facilitating research and preparing for real-time situations.
We aim to delve into how they fortify medical imaging analysis of MRIs, CT, and X-ray scans, bolstering the detection and diagnosis of neurological afflictions, including brain tumors and strokes. Simultaneously, we'll discuss the role of image synthesis in creating realistic depictions of neurological conditions and potential surgeries, facilitating advancements in research and clinical preparation. With this, we aspire to showcase how these cutting-edge technologies are revolutionizing neurological investigations and improving prognosis, ultimately underscoring their significance in the field.
The scope of this Research Topic covers the amalgamation of computer vision, image synthesis, and neurological perspectives. Specific themes include, but is not limited to:
-Improvements in image processing, analysis, and segmentation techniques for neurological imaging.
-Innovative algorithms and structures for brain lesion identification, quantification, and tracking.
-Applications and effects of deep learning on neurology regarding diagnosis, treatment plans, and prognosis.
-Image synthesis utilities in simulating neurological disorders and surgeries.
-Integration of computer vision and image synthesis in tailored therapy planning and evaluation.
-Ethical, legal, and social implications of employing computer vision and image synthesis in neurology.
Manuscripts dealing with innovative deep learning algorithms for diagnosis, treatment plan, and prognosis of neurological afflictions fall within the scope of Frontiers in Computational Neuroscience. Manuscripts related to improvements in Image processing fall within the scope of the Image Processing section and all the manuscripts mainly dealing with the Neurological applications fall within the scope of the Neurotechnology section.
We welcome various manuscript types including, but not limited to: Review, Original Research, Manuscript Summary, Method, Perspective, Correction, Data Report, Technology and Code, Opinion, Brief Research Report, General Commentary, and Hypothesis and Theory.
