Quantitative imaging techniques ( CT/ MR/ X-Ray / PET) allow the evaluation of different aspects of brain structures and in some modalities micro structures, metabolites and bio-markers in different pathologies such as Dementia, Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), Epilepsy, Traumatic Brain Injury (TBI), Tumors and other Central Nervous System (CNS) disorders. Providing significant information about the CNS disorders and Brain pathologies are very essential in tracking these diseases during a period of time.
Diagnostic errors, qualitative reports and lesion detections have been a very challenging area for measurement due to variety of diseases, lesion features (size, shape and structure) and user dependent radiological reports. Using the latest technologies in diagnosis including: Artificial Intelligence (AI) , Machine Learning (ML), Radiomics, Image Analysis methods and others have led us to an accurate diagnosis and treatment. In this Research Topic one of the most important aims is focusing on the incidence and nature (such as the cause and risks) of diagnostic errors in radiological procedure. To bring a real example for this can be a measuring error due to lack of knowledge in measuring the volume of MS plaques and comparison with previous studies.
This Research Topic welcomes articles that focus on artificial quantitative neuroradiological methods such as machine learning (ML) and radiomics as well as the role of Artificial Intelligence (AI) within that. The themes that we are interested in include, but is not limited to :
- Advanced Analysis of Neuroimaging modalities
- Quantitative measurements
- Ethics in using AI in radiology
- Volumetric MR/CT images
- Structural Reporting in Radiology
- Methodological researches in radiology field
- Application of medical imaging in all neurological disorders such as ALS, Tumors, AD, Psychological etc.
- Automated quality control tools
- MRS, fMRI, DTI, Perfusion, MR flowmetery, CT/ MR Angiography, and all other modalities
We acknowledge that Mr. Mojtaba Barzegar, Medical Physicist, from Tehran University of Medical Sciences acted as the Topic Coordinator for the preparation of this Research Topic. He is currently carrying out his fellowship for Alzheimer’s disease, Psychiatric and Neuroradiology at Society for Brain mapping and Therapeutics (SBMT) as one the best societies in strategical planning in Neuroscience and prevention the related disorders.
Quantitative imaging techniques ( CT/ MR/ X-Ray / PET) allow the evaluation of different aspects of brain structures and in some modalities micro structures, metabolites and bio-markers in different pathologies such as Dementia, Multiple Sclerosis (MS), Amyotrophic Lateral Sclerosis (ALS), Epilepsy, Traumatic Brain Injury (TBI), Tumors and other Central Nervous System (CNS) disorders. Providing significant information about the CNS disorders and Brain pathologies are very essential in tracking these diseases during a period of time.
Diagnostic errors, qualitative reports and lesion detections have been a very challenging area for measurement due to variety of diseases, lesion features (size, shape and structure) and user dependent radiological reports. Using the latest technologies in diagnosis including: Artificial Intelligence (AI) , Machine Learning (ML), Radiomics, Image Analysis methods and others have led us to an accurate diagnosis and treatment. In this Research Topic one of the most important aims is focusing on the incidence and nature (such as the cause and risks) of diagnostic errors in radiological procedure. To bring a real example for this can be a measuring error due to lack of knowledge in measuring the volume of MS plaques and comparison with previous studies.
This Research Topic welcomes articles that focus on artificial quantitative neuroradiological methods such as machine learning (ML) and radiomics as well as the role of Artificial Intelligence (AI) within that. The themes that we are interested in include, but is not limited to :
- Advanced Analysis of Neuroimaging modalities
- Quantitative measurements
- Ethics in using AI in radiology
- Volumetric MR/CT images
- Structural Reporting in Radiology
- Methodological researches in radiology field
- Application of medical imaging in all neurological disorders such as ALS, Tumors, AD, Psychological etc.
- Automated quality control tools
- MRS, fMRI, DTI, Perfusion, MR flowmetery, CT/ MR Angiography, and all other modalities
We acknowledge that Mr. Mojtaba Barzegar, Medical Physicist, from Tehran University of Medical Sciences acted as the Topic Coordinator for the preparation of this Research Topic. He is currently carrying out his fellowship for Alzheimer’s disease, Psychiatric and Neuroradiology at Society for Brain mapping and Therapeutics (SBMT) as one the best societies in strategical planning in Neuroscience and prevention the related disorders.
