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The Emerging Imaging Technologies and Applications [EITA] study section reviews proposals seeking to optimize and refine newly developed imaging technologies or methods for specific uses, e.g. to target specific tissues, pathologies or biological processes.

EITA reviews proposals to create protocols and methods for applying or validating new and emerging technologies intended for use in living animals and/or humans. The envisioned use of the technology may be clinical but may also be basic biological research, without any evidence of translational application.


The List of Reviewers lists all present, whether standing members or temporary, to provide the full scope of expertise present on that date. Lists are posted 30 days before the meeting and are tentative, pending any last minute changes.

Review Dates

Membership Panel

The membership panel is a list of chartered members only.


  • Studies emphasizing optimization of newly developed methodologies
  • Efforts to advance image display, post processing algorithms and methods
  • Disease-based optimization of emerging technologies
  • Investigation of new imaging methods using human data sets
  • Translational applications advancing methods from animal models to human
  • Artificial intelligence and machine learning approaches to quantifying and extracting information from images, feature detection, classification problems, and computer-aided diagnosis
  • Methodologies for signal and image processing toward enhancing image perception, visualization, reconstruction, and quantitation
  • Task performance assessment

Shared Interests and Overlaps

EImaging Technology Development [ITD] reviews closely related developmental imaging proposals. The distinction is in the stage of development; when the emphasis is on the basic capabilities of an imaging system, review is generally done in ITD. When the emphasis is on optimization of a method for a particular clinical use, target pathology, or research question, review is generally done in EITA. Machine learning and artificial intelligence approaches to image analysis are reviewed by EITA; development of new computational models using standard algorithms is reviewed in EITA whereas creation of new computational approaches to imaging data is reviewed in ITD.

Clinical Translational Imaging Science [CTIS] also reviews developmental imaging proposals. EITA reviews applications where the emphasis is on engineering or computational approaches to optimizing emerging imaging systems for a particular use, often using animal models. When the work has advanced to the point where testing in humans with clinical outcomes is proposed, it is typically reviewed in CTIS.

Emerging Imaging Technologies in Neuroscience (EITN) reviews proposals to develop imaging systems for specific biological, physiological, and disease targets in the nervous system. If the characteristics of the nervous system are critical to the proposed work, the application will usually be reviewed in EITN. If the emphasis is on development at a level where neuroscience is less central it may be reviewed in EITA.

Imaging Guided Interventions and Surgery [IGIS] also reviews applications proposing to develop or optimize imaging systems for specific biological, physiological, and disease targets. When the aim of technical development is image-based guidance of a therapeutic intervention, and the proposal includes evaluation of that intervention (even in a preclinical context), the work is likely to be reviewed in IGIS.

Biomedical Computing and Health Informatics Study Section [BCHI] reviews applications which focus on the development, validation, and use of computing or informatics systems integrating data from multiple datasets, including imaging, for clinical decision making. Applications that develop analysis methods and tools for feature detection and classification in imaging datasets are reviewed in EITA.

Biodata Management and Analysis[BDMA] There are shared interests with EITA with regard to image analysis. Applications that focus on the maintenance, refinement, or integration of existing software tools for imaging datasets will be reviewed in BDMA. Applications that develop new data analysis methods and tools for imaging post processing and display, feature detection, and classification will be reviewed in EITA.

Biostatistical Methods and Research Design [BMRD] reviews applications which seek to advance statistical and mathematical techniques and technologies applicable to biomedical data. There are shared interests with EITA in data analysis and methodology/software development. Applications which focus on the development of scalable statistical methods for analysis of imaging datasets or the development and dissemination of statistical methods as software packages are typically reviewed in BMRD. Applications which focus on new software and database development as related to image acquisition, processing, reconstruction, or analysis are typically reviewed in EITA.

Clinical Neuroscience and Neurodegeneration [CNN] reviews applications that use neuroimaging (MRI, DTI, MRS, PET and fMRI, etc), to identify molecular, anatomical or neuropathological biomarkers in the context of investigating risk, onset, progression, and treatment response in neurodegenerative disease. If instead the emphasis is on the development/optimization of imaging technologies and/or on the development/optimization of software and analytical methods for image analysis at a level where neuroscience is less central, the applications are reviewed in EITA.

Acute Neural Injury and Epilepsy [ANIE] reviews applications that use imaging approaches for the diagnosis, staging, and tracking of disease in epilepsy, traumatic brain injury, spinal cord injury and stroke. If instead the emphasis is on the development/optimization of imaging technologies and/or on the development/optimization of software and analytical methods for image analysis at a level where neuroscience is less central, the applications are reviewed in EITA.