Journal of Medical Imaging

Editor-in-Chief: Maryellen L. Giger, The University of Chicago

The Journal of Medical Imaging covers fundamental and translational research, as well as applications, focused on medical imaging, which continue to yield physical and biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal.

Calls For Papers
How to Submit a Manuscript

Regular papers: Submissions of regular papers are always welcome.

Special section papers: Open calls for papers are listed below. A cover letter indicating that the submission is intended for a particular special section should be included with the paper.

To submit a paper, please prepare the manuscript according to the journal guidelines and use the online submission systemLeaving site. All papers will be peer‐reviewed in accordance with the journal's established policies and procedures. Authors have the choice to publish with open access.

X-Ray Computed Tomography at 50
Publication Date
Vol. 8, No. 5
Submission Deadline
1 November 2020
Guest Editors
Norbert J. Pelc, Sc.D.

Stanford University
Department of Radiology
E-mail: pelc@stanford.edu

Rebecca Fahrig, PhD

Siemens Healthineers
E-mail:  rebecca.fahrig@siemens.com

Patrick La Riviere, PhD

University of Chicago
E-mail: pjlarivi@uchicago.edu

Scope

The first patient imaging exam with X-ray Computed Tomography (CT) was performed on October 1, 1971.  We are thus about to celebrate the 50th anniversary of this powerful technology that revolutionized diagnostic imaging. In its early years, CT quickly replaced a number of more invasive and less effective tests, and, in the ensuing years, the clinical impact of CT became even more compelling as the performance of clinical CT systems continued to progress at an impressive rate, while also improving dose efficiency. Exciting current research promises years of continued progress through advances in components, system designs, algorithms, and clinical applications, which will further improve the clinical utility of CT while simultaneously reducing patient dose.

This special section of the Journal of Medical Imaging, while including a few invited historical papers, seeks contributions in the form of research articles on the subject of X-ray Computed Tomography that highlight a wide spectrum of research areas including, but not limited to:

  • new detectors
  • new systems or system components
  • spectral CT
  • cone-beam CT
  • special-purpose systems
  • image reconstruction
  • quantitative imaging
  • image analysis
  • applications.

For more information on submission please see the journal web site at http://spie.org/JMIauthorinfo. Please indicate in your cover letter that the submission is for this special section. All submissions will be peer-reviewed.

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. Please indicate in your cover letter that the submission is for this special section.

Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened for publication once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

2D and 3D Imaging: Perspectives in Human and Model Observer Performance
Publication Date
Vol. 8, No. 4
Submission Deadline
30 November 2020
Guest Editors
Claudia Mello-Thoms, PhD

University of Iowa
Department of Radiology
Email: claudia-mello-thoms@uiowa.edu

Craig Abbey, PhD

University of California Santa Barbara
Department of Psychology and Brain Sciences
Email: craig.abbey@psych.ucsb.edu

Elizabeth A. Krupinski, PhD

Emory University
Department of Radiology and Imaging Sciences
Email: ekrupin@emory.edu



Scope

Traditional studies in medical image perception have been conducted using 2D images, such as chest radiographs and mammograms. However, as volumetric (3D) imaging has become more widely used in radiology, there is a paucity of information about how observers interact with these images to render clinical decisions.

The theme of this special section is the characterization of differences between the use of 2D and 3D imaging as it relates to improved understanding of human decision-making processes, including, but not limited to:

  • visual search,
  • image perception,
  • observer performance,
  • human and model observers,
  • cognitive processes,
  • image understanding.

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Radiogenomics

Radiogenomics in Prognosis and Treatment
Publication Date
Vol. 8, No. 1
Submission Deadline
1 April 2020
Guest Editors
Karen Drukker, PhD

University of Chicago
Department of Radiology
Email: kdrukker@uchicago.edu

Despina Kontos, PhD

University of Pennsylvania
Department of Radiology
Email: Despina.Kontos@uphs.upenn.edu

Hui Li, PhD

University of Chicago
Department of Radiology
Email: huili@uchicago.edu

Scope

Radiogenomics, or ‘imaging genomics’ in the context here, is a rapidly evolving field seeking correlations between computer-extracted imaging phenotypes and underlying genetic mechanisms. In other words, in cancer-related research, radiogenomics examines the relationship between the imaging phenotypes of cancers — imaged with, for example, MRI or CT — and gene expression patterns, gene mutations or variations, genetic pathways, and other genome-related characteristics. Similar associations could be investigated in other conditions such as Alzheimer’s disease.

Imaging plays an important role in the management of patients, including diagnosis, staging, radiation treatment planning, evaluation and prediction of response to therapeutics, and disease monitoring. With the recent increase in the availability of high-quality imaging data and improvements in computation power, radiomics has recently evolved beyond disease detection and diagnosis to the discovery of new imaging biomarkers, or imaging phenotypes, relevant to various aspects of clinical imaging. For example, cancer is a complex disease and one of the cornerstones to understanding cancer is genomics, that is, the research of genes and their inter relationships in order to identify their combined influence on cancer development and progression. The integration of radiomics and genomics into radiogenomics has great potential to discover, and better understand, relationships between imaging phenotypes and the biological underpinnings of disease to further improve the prediction of clinical outcomes.

Radiogenomics

The goal of this JMI special section is to pull together recent research on radiogenomics to illustrate both progress and challenges. This JMI special section is open to all radiogenomics-related research investigations, but especially encourages relevant submissions for (but not limited to) the following topics:

  • Review articles on radiogenomics
  • Pipelines for image processing and computational aspects
  • Research using publicly available datasets (such as the Cancer Genome Atlas and the Cancer Imaging Archive)
  • Dataset requirements for radiogenomics for reproducibility and generalizability
  • Practical significance of radiogenomics in improving patient outcomes
  • Radiogenomics for precision medicine and radiotherapy
  • Radiogenomics for characterizing tumor heterogeneity
  • Emerging analytical image-based paradigms for clinical oncology
  • Potential role for deep learning in radiogenomics

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Virtual Clinical Trials
Publication Date
Vol. 7, No. 4
Submission Deadline
Closed for submissions.
Guest Editors
Paul Kinahan, PhD

University of Washington
Department of Radiology
Email: kinahan@uw.edu

Andrew Maidment, PhD

University of Pennsylvania
Department of Radiology
Email: Andrew.Maidment@uphs.upeen.edu

Robert Nishikawa, PhD

University of Pittsburgh
Department of Radiology
Email: nishikawarm@upmc.edu

Ehsan Samei, PhD

Duke University Medical Center
Department of Radiology
Email: ehsan.samei@duke.edu

Scope



Clinical trials and clinical studies are expensive and time consuming. This is problematic for developing new imaging technology and imaging biomarkers. The development of an imaging technology or biomarker may involve optimizing many parameters simultaneously, and thus it is not practical to do so using a clinical trial, even though ultimately, the new technology or biomarker must be evaluated through a clinical trial.

It is now possible to simulate individuals and specific pathologies from the population of all humans with increasingly higher accuracy. This, together with advanced models of image simulation, image processing and image reconstruction, means that we can create arbitrarily large databases of simulated images. By combining these advances with advances in model observer methods, it is both possible and useful to conduct virtual clinical trials for optimization and for estimating the impact of a new imaging technology. Using a series of linked simulations, the impact of each step in the entire imaging chain from biology to study result can be evaluated.

We define a virtual clinical trial as a combination of the following steps: (1) establish ground truth, (2) forward model the image generation, (3) apply model observers, and (4) analyze the imaging results against the ground truth. Each step has a series of sub-components that require individual simulations; each simulation has uncertainties or parameter variations that must be taken into account. While this is a nascent field, there have been an increasing number of studies as well as short courses in different medical imaging subfields (i.e., Mammography, CT , PET).

The goal of this JMI special section is to pull together recent research on virtual clinical trials from different medical imaging subfields to illustrate both progress and commonalities.

This JMI special is open to everyone, and especially encourages relevant submissions for (but not limited to) the following topics:

  • Review articles
  • Specific medical imaging subfield research (i.e. mammography, CT, PET)
  • Metrics and standards for reporting
  • Variability in the biological/patient, acquisition, image reconstruction, processing, and interpretation components
  • Pipelines for processing
  • Computation aspects

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Three-Dimensional Image Reconstruction in Nuclear Medicine, PET, and CT
Publication Date
Vol. 7, No. 3
Submission Deadline
Closed for submissions.
Guest Editors
Scott D. Metzler, PhD

University of Pennsylvania
Department of Radiology
Email: metzler@upenn.edu

Samuel Matej, PhD

University of Pennsylvania
Department of Radiology
Email: matej@pennmedicine.upenn.edu

J. Webster Stayman, PhD

Johns Hopkins School of Medicine
Department of Biomedical Engineering
Email: web.stayman@jhu.edu

Scope

Image reconstruction is a critical component of the diagnostic modalities of nuclear medicine, PET, and CT. This JMI special issue focuses on innovative uses of reconstruction of their application in these modalities. Other areas of interest are the use of deep learning methods in addressing issues related to reconstruction in these methods or the use of hardware acceleration techniques

This special section is open to everyone, and but especially encourages relevant submissions from the 15th International Meeting on Fully Three-Dimensional Image Reconstruction ( www.fully3d.org). This conference is a biennial conference dedicated to bringing together a diverse group of researchers, who are jointly committed to developing, validating, and translating these technologies into clinical practice.

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

Interventional and Surgical Data Science
Publication Date
Vol. 7, No. 3
Submission Deadline
Closed for submissions.
Guest Editors
Amber L. Simpson, PhD

Queen's University
Ontario, Canada
Email: amber.simpson@queensu.ca
http://simpsonlab.org/

Michael I. Miga, PhD

Vanderbilt University
Department of Biomedical Engineering
Nashville, Tennessee, United States
E-mail: michael.i.miga@Vanderbilt.Edu
https://engineering.vanderbilt.edu/bio/michael-miga

Scope

ISDS

This special section of the Journal of Medical Imaging is focused on a new emerging area of research called interventional and surgical data science. Recognizing the long-history of procedural data-science work originating from the Medical Imaging Conference on Image-Guided Procedures, Robotic Interventions, and Modeling, the special section will feature data-driven technologies for the delivery, measurement, and monitoring of therapy. The curation of this procedural medicine data to develop best practices in training, planning, delivery of therapy, and post-operative care is, to a great degree, an unexplored topic with potentially profound impact to the trajectory of patient care.

Original papers are requested in the following topic areas specifically for the engineering of surgical and interventional systems associated with data-driven changes in procedural medicine:

• Data-driven procedural workflow optimization, and novel instrumented procedural rooms
• Multi-scale integration of procedural data
• Novel data-guided technology frameworks
• Tissue/disease characterization
• Integration of biomedical data
• Data-driven computational modeling
• Integrated imaging omics models toward surgical/interventional selection or outcomes
• AI approaches for data integration
• Evaluation frameworks for data-driven surgery or intervention
• Data-driven models for predicting procedural medicine outcomes
• Integration of intraoperative/interventional imaging (including molecular)
• Clinical applications and technology integration
• Data science and visualization
• Data-driven computer-assisted surgery and therapy planning
• Data curation
• Surgical process modeling
• Data and training paradigms for procedural medicine
• Other related areas

It is required that submitted manuscripts include a brief section called “Impact on Interventional and Surgical Data Science” describing the influence of their work on procedural decision making. These sections will be central for construction of the editorial introduction of the special issue in an effort toward consensus in this burgeoning field.

Members from the conference committee for the Medical Imaging Conference on Image-Guided Procedures, Robotic Interventions, and Modeling will act as associate editors for submitted manuscripts. If needed, additional associate editors may be asked to participate to ensure rigorous and salient review.

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. Please indicate in your cover letter that the submission is for this special issue.

Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

As an additional benefit, all papers accepted to this special section will be invited to participate at SPIE Medical Imaging 2020 Image-Guided Procedures, Robotic Interventions, and Modeling Conference (participation is optional). Invited authors will be provided the opportunity to write a ‘Technical Note’ about their accepted paper which will be published in the conference proceedings. In addition, with sufficient submissions, a special session of oral platform presentations from accepted papers will be held during the conference. Other accepted papers will be provided platform or poster presentations in the standard conference tracks designated with high distinction.

Medical Image Perception and Observer Performance
Publication Date
Vol. 7, No. 2
Submission Deadline
Closed for submissions.
Guest Editors
Elizabeth A. Krupinski, PhD

Emory University
Department of Radiology & Imaging Sciences
1364 Clifton Road NE
Atlanta, Georgia 30322, USA
E-mail: ekrupin@emory.edu  

Scope

Medical image perception research measures the human observer's ability to perform specific diagnostic tasks using real or simulated medical images and compares the observer performance with predictions from quantitative models.

The theme of this special section is image perception and observer performance research on detection and discrimination of abnormalities; cognition, psychophysics, and behavior; perception errors; visual search patterns; human and ideal observer models; computer-based perception; impact of display and ergonomics; image processing; and assessment methods, metrics, and statistics. Although radiology imaging is a key focus, we are particularly interested in articles that deal with other medical imaging specialty applications such as pathology, ophthalmology, dermatology, and telemedicine.

This special section is open to everyone, and but especially encourages relevant submissions from the Medical Image Perception Conference (MIPS XVIII) . The Medical Image Perception Conference is a biennial conference dedicated to bringing together people interested in human and computer perception of medical image information and related subjects, such as detection and discrimination of abnormalities, cognitive and psychophysical processes, perception errors, search patterns, human and ideal observer models, computer-based perception (CAD and CADx), impact of display and ergonomic factors on image perception and performance, role of image processing on image perception and performance, and assessment methodologies.

Medical Image Perception and Observer Performance

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

NOTE: Publication is currently in progress for this special section of Volume 7, Issue 2.

Evaluation Methodologies for Clinical AI
Publication Date
Vol. 7, No. 1
Submission Deadline
Closed for submissions.
Guest Editors
Susan M. Astley, PhD

University of Manchester
Division of Informatics, Imaging & Data Sciences
E-mail: sue.astley@manchester.ac.uk

Weijie Chen, PhD

U.S. Food and Drug Administration
Email: Weijie.Chen@fda.hhs.gov

Kyle J. Myers, PhD

U.S. Food and Drug Administration
Email: Kyle.Myers@fda.hhs.gov

Robert M. Nishikawa, PhD

University of Pittsburgh
E-mail: nishikawarm@upmc.edu

Scope

With the explosion of deep learning applications in medical imaging there is an urgent need to develop methods to evaluate the performance of artificial intelligence (AI) systems due to the increased complexities/varieties of AI technologies and the dependence of these new technologies on large datasets. Proper testing methodology, metrics, and training/validation/testing study designs are needed to ensure that studies produce meaningful, robust, and generalizable results.

The goal of this JMI special issue is to pull together recent research on evaluation methodologies and clinical studies that will help to define proper methods and good practice consensus for evaluating artificial intelligent systems clinically.

This JMI special issue is open to everyone, and especially encourages relevant submissions for (but not limited to) the following topics specifically geared towards AI:

ClinicalAI

Evaluation studies 

  • Clinical studies or empirical data, e.g., prospective clinical studies, retrospective clinical studies, case-control studies, observer studies

  • Comparison of AI with human clinicians/observers

  • Evaluation of continuously learning AI systems

Statistical evaluation methodologies, e.g.,

  • Novel metrics or standards

  • Use of simulated images or data

  • Modeling

Image quality, reproducibility, robustness, generalizability, and usability, e.g.,

  • Evaluation of AI as model observers for image quality assessment

  • Evaluation of data augmentation, annotation, training methods, and other technical factors that affect AI performance

  • Evaluation of robustness of AI algorithms to different image acquisition protocols

Review articles.

Manuscripts should conform to the author guidelines of the Journal of Medical Imaging. Prospective authors should submit an electronic copy of their manuscript through the online submission system at https://jmi.msubmit.net. The special section should be mentioned in the cover letter. Each manuscript will be reviewed by at least two independent reviewers. Peer review will commence immediately upon manuscript submission, with a goal of making a first decision within six weeks. Special sections are opened online once a minimum of four papers have been accepted; each paper is published as soon as the copyedited and typeset proofs are approved by the author.

NOTE: Publication is currently in progress for this special section of Volume 7, Issue 1.

Published Special Sections

Advances in Breast Imaging (July-September 2019)
Guest Editors: Elizabeth A. Krupinski, Susan Astley, Martin Tornai, Robert Marti, and Reyer Zwiggelaar

3D Printing in Medical Imaging (April-June 2019)
Guest Editors: Ehsan Samei and Joseph Lo

Artificial Intelligence in Medical Imaging (January-March 2019)
Guest Editors: Paul Kinahan, Patrick La Riviere, and Elizabeth A. Krupinski

Medical Image Perceptions and Observer Performance (July-September 2018)
Guest Editors: Elizabeth A. Krupinski, Mia K. Markey, and Tamara Miner Haygood

Image-Guided Procedures, Robotic Interventions, and Modeling (April-June 2018)
Guest Editors: Michael I. Miga and Amber L. Simpson

Quantitative Imaging Methods and Translational Developments-Honoring the Memory of Dr. Larry Clarke (January-March 2018)
Guest Editors:  Robert Nordstrom, Darrell Tata, Lawrence Schwartz, Lubomir Hadjiyski, and Maryellen Giger

Radiomics and Deep Learning (October-December 2017)
Guest Editors: Despina Kontos, Ronald M. Summers, and Maryellen Giger

Visions of Safety: Perspectives on Radiation Exposure (July-September 2017)
Guest Editors:  Ehsan Samei and Christoph Hoeschen 

Digital Pathology (April-June 2017)
Guest Editors: Metin N. Gurcan, Anant Madabhushi, and John Tomaszewski

Development, Challenges, and Opportunities of Positron Emission Tomography (January-March 2017)
Guest Editors: Norbert J. Pelc, Paul E. Kinahan, and Roderic I. Pettigrew

Medical Image Perception and Observer Performance (January-March 2016)
Guest Editor: Elizabeth A. Krupinski

Radiomics and Imaging Genomics (October-December 2015)
Guest Editors: Maryellen Giger and Sandy Napel

Pioneers in Medical Imaging: Honoring the Memory of Robert F. Wagner (October-December 2014)
Guest Editors: Kyle J. Myers and Weijie Chen

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