Medical Image Reconstruction and Big Data Analysis for Neurological Disorders

It is well-known that neurological disorders are the type of disease characterized by the disruption of regular operations of brain functions. Broadly speaking, neurological disorders include epilepsy, Alzheimer’s disease (AD), Parkinson’s disease (PD) and schizophrenia (SZ), stroke, multiple sclerosis (MS), tuberous sclerosis complex (TSC), focal cortical dysplasia (FCD), cerebral tumor and so on. The neurological disorders account for a heavy burden on both the whole families and the social health system. If the patient suffers from the neurological disorders, the impact on the whole family relationship is significant. Therefore, it is critical to detect these disorders at an early stage so that their doctors can develop individualized treatment plans with a high chance of cure. In order to reach this aim, a wide variety of imaging techniques have been developed (such as ultrasound (US), magnetic resonance imaging (MRI), computed tomography (CT), positron emission tomography (PET), optical imaging, etc.). These techniques allow us to acquire enormous amounts of medical data, which can be used to detect these disorders and plan appropriate treatments at an early stage.

To adopt the huge amount of medical data, some high-efficient and automatic algorithms need to be studied to reconstruct images and analyze big data It is necessary to study high-performance and automatic algorithms to reconstruct the images and processing the large amount of medical data These algorithms, additionally, will also enable doctors and scientists to intuitively understand the data through the transformation of visual image information into deep features for quantitative research. It not only has a wide range of clinical neurological applications, but also provides a great scientific and intuitive basis for the diagnosis of neurological diseases. Moreover, these schemes in clinical neurological applications should balance the trade-offs between the accuracy and the efficiency.

The aim of this Research Topic is to bring together original research and review articles discussing recent medical image reconstruction and big data analysis for neurological disorders. We welcome all types of submissions related to data acquisition, computational methods, software tools and clinical applications for the detection and treatment of neurological disorders.

Potential topics include but are not limited as follows:

· New investigation tools for neurological diseases

· Computer aided diagnosis systems for neurological disorders

· Advanced image acquisition techniques

· Medical Image Reconstruction for Neurological Disorders

· Big Data Analysis for Neurological Disorders

· Feature representation learning and radiomics study

· Machine learning and deep learning for medical big related to neurological disorders

· Medical big data acquisition and visualization methods

· Clinical treatment outcome evaluations of neurological disorders

· Clinical case reports of neurological disorders

Keywords: Big data, Medical Image Reconstruction, neurological disorders, MRI, CT, PET, medical data, automatic alrorithms

Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.