Journal of Medical Imaging

Editor-in-Chief: Bennett A. Landman, Vanderbilt University, USA

The Journal of Medical Imaging (JMI) allows for the peer-reviewed communication and archiving of fundamental and translational research, as well as applications, focused on medical imaging, a field that continues to benefit from technological improvements and yield biomedical advancements in the early detection, diagnostics, and therapy of disease as well as in the understanding of normal conditions.

On the cover: 3D virtual cardiac model, from the article "Augmented and virtual reality imaging for collaborative planning of structural cardiovascular interventions: a proof-of-concept and validation study" by X. Jacquemyn, K. Bamps, et al., in the JMI Special Section on AR/VR in Medical Imaging, edited by Ryan Beams (US FDA) and Raj Shekhar (Children’s National Hospital) for Volume 11 Issue 6.

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.

Medical Image Perception and Observer Performance
Publication Date
Vol. 12
Submission Deadline
Submissions due by 20 December 2024
Guest Editors
Frank Tong, PhD

Vanderbilt University
Email: frank.tong@Vanderbilt.Edu

Emory University School of Medicine, USA
Email: elizabeth.anne.krupinski@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 issue 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 issue is open to everyone, and especially encourages relevant submissions from the Medical Image Perception Conference (MIPS XX). 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/AI, impact of display and ergonomic factors on image perception and performance, role of image processing on image perception and performance, and assessment methodologies.

Manuscripts should conform to the JMI author guidelineshttp://spie.org/JMIauthorinfo. 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.

Medical Image Perception and Observer Performance JMI Call for Papers

 

Advances in Breast Imaging
Publication Date
Vol. 12
Submission Deadline
1 January 2025
Guest Editors

University of Chicago
Email: m-giger@uchicago.edu

University of Manchester
Email: sue.astley@manchester.ac.uk

University of Chicago
Email: kdrukker@uchicago.edu

University of Chicago
Email: huili@uchicago.edu

University of Pennsylvania 
Email: Andrew.Maidment@pennmedicine.upenn.edu

University of Chicago
Email: hwhitney@uchicago.edu

Scope

Advances in breast cancer imaging include the latest physical-technical developments, quality control aspects, and clinical experiences with novel breast imaging technologies, including digital mammography, tomosynthesis, breast CT, MR, ultrasound, optical, and molecular imaging for early

This JMI special issue will focus on research in digital mammography, digital breast tomosynthesis, CT, MRI, ultrasound, optical imaging, molecular imaging, pathological imaging, multimodality imaging, theranostics, image processing, image reconstruction, visualization, computer-aided diagnosis and therapy, quantitative imaging, radiomics, deep learning, system design, image quality, observer performance, human factors and workflow, breast density, clinical evaluation, and virtual, in silico, and modeling clinical trials.

This JMI special issue is open to everyone, yet especially encourages relevant submissions from the 17th International Workshop on Breast Imaging (IWBI), recently held at the University of Chicago in 2024. The IWBI is designed as a platform to present the latest technological and machine intelligence developments and clinical experiences of novel breast imaging technologies, bringing together a diverse group of researchers, clinicians, and representatives of industry, who are jointly committed to developing technology for the early detection and subsequent patient management of breast cancer.

Manuscripts should conform to the JMI author guidelineshttp://spie.org/JMIauthorinfo. 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.

Advances in Breast Imaging; image credit: Douglas et al., doi 10.1117/1.JMI.11.3.034501

 

Computational Pathology
Publication Date
Vol. 12
Submission Deadline
Submissions due by 15 March 2025
Guest Editors

UT Dallas and UT Southwestern, USA
Email: bfei@utdallas.edu

Wake Forest University School of Medicine, USA
Email: mgurcan@wakehealth.edu

Vanderbilt University, USA
Email: yuankai.huo@vanderbilt.edu

University of Florida, USA
Email: pinaki.sarder@ufl.edu

Western University, Canada
Email: aaron.ward@uwo.ca

Scope

The development of large-scale pathological image analysis algorithms is essential for enhancing patient outcomes and propelling advancements in healthcare. With the burgeoning availability of big data in computational pathology, there exists a significant opportunity to craft more precise and individualized diagnostic and treatment strategies. However, the complexity and diversity of digital pathological images and their varying modalities present substantial challenges in devising scalable image processing frameworks capable of managing inter-subject variations and delivering robust, timely medical image analysis. At the same time, ethical implementation of the underlying tools is of paramount interest, to ensure addressing model bias, data imbalance, fairness, and transparency, requiring usability and co-design approaches to be integrated with computational pipeline development.

To overcome these hurdles, it is imperative to foster interdisciplinary collaborations among engineers, scientists, clinicians, medical AI ethicists, and human factor researchers. By uniting the expertise of these professionals, innovative methods for data analysis, management, and sharing can be developed to optimize the utilization of big data in computational pathology. Moreover, advancements in large-scale data processing and sophisticated foundation models can assist in discerning patterns and relationships between imaging characteristics and clinical outcomes, thus enhancing the accuracy of diagnoses and tailoring treatment plans more effectively to empower various stakeholders, including clinicians and patients. 

While the directions for computational pathology are shaping up, the development of large-scale pathological image analysis algorithms has not kept pace with the increasing sophistication and complexity of image modalities. It is crucial, therefore, to prioritize the creation of patient-centered clinical image analysis frameworks that incorporate large-scale data, models, and infrastructures. These systems must be robust yet capable of rapid processing to support timely decision-making in clinical settings. There is a pressing need for the development of fast, efficient algorithms that can handle extensive volumes of digital pathologic data. Similarly, the tools developed need to be codesigned with important stakeholders, including patients and clinicians, ensuring providing critical support in clinical decision making and ultimately improving the speed and accuracy of patient care interventions.

This JMI special section welcomes original research papers that develop new methods for computational pathology with large-scale data, models, and infrastructures. We also welcome high-quality submissions from work presented at top conferences, such as MICCAI, IPMI, MIDL, CVPR, ICLR, ICML, and others, that propose new methods and techniques for leveraging patient-centered clinical image analysis with large-scale data, models, and infrastructures. Topics of interest include, but are not limited to, the following:

Computational pathology algorithms

  • Patient-centered clinical image analysis with image and non-image data analysis
  • Domain adaptation techniques for transferring models across different clinical domains
  • Deep learning for pathological image analysis using large datasets
  • The development of fast and efficient algorithms that can process large amounts of pathological imaging data in point-of-care decision support
  • Multi-omics and texture analysis using digital pathology
  • Personalized medicine using digital pathology data
  • Big Data analytics for image-guided therapies
  • Explainable AI techniques for clinical decision-making using foundation models
  • Privacy-preserving techniques for using foundation models in clinical image analysis
  • Quality assurance and quality control in digital pathology studies
  • Ethical AI development in computational pathology
  • Usability and co-design study in to enhance computational pathology pipeline

Clinical digital pathology image analysis with large-scale deep learning models

  • Developing models for clinical outcomes using large-scale digital pathology datasets
  • Efficient fine-tuning methods for clinical applications using foundation models
  • Evaluating and benchmarking foundation models for digital pathology image analysis applications
  • Developing foundation models for real-time image analysis in clinical settings
  • Adapting foundation models for rare disease diagnosis and treatment planning

Computational Pathology with advanced computational infrastructures

  • Developing algorithms for data standardization and harmonization in multi-site studies
  • Developing federated learning and distributed computing frameworks for large-scale digital pathology imaging datasets
  • Federated learning methods for computational pathology
  • The development of fast and efficient infrastructures that can process large amounts of pathological image data in point-of-care decision support
  • Developing automated computational pathology pipelines for large-scale medical imaging studies and deployment

Manuscripts should conform to the JMI author guidelineshttp://spie.org/JMIauthorinfo. 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.

Computational Pathology; image generated by editors via GPT4

 

Theranostics
Publication Date
Vol. 12
Submission Deadline
13 March 2025
Guest Editors

University of Texas MD Anderson Cancer Center
Email: skappadath@mdanderson.org

Darko Pucar, PhD

Yale University 
Email: darko.pucar@yale.edu

University of Chicago 
Email: hwhitney@uchicago.edu

Yan Zhuang, PhD

National Institutes of Health Clinical Center 
Email: yan.zhuang2@nih.gov

Scope

Theranostics, the combination of the terms therapeutics and diagnostics, is an emerging field of medicine that uses a radiopharmaceutical to identify and locate disease based on specific targets or receptors (diagnosis), followed by a second radiopharmaceutical to deliver therapeutic levels of radiation absorbed dose to target tissue (therapy).  Building upon its foundation in nuclear medicine, more recently the field has gained additional attention because of demonstrations of its ability to improve patient outcomes with low side effects. Successful clinical applications of theranostics include treatments for neuroendocrine tumors and prostate cancer.

Medical imaging plays a vital role in theranostics. In addition to the critical role imaging plays in disease diagnosis, staging, monitoring, and response evaluation, accurate visualization of in vivo radiopharmaceutical biodistribution provides critical information on patient selection for theranostics. Theranostics can incorporate ultrasound, magnetic resonance imaging (MRI), computed tomography (CT), positron-emission tomography (PET), single-photon emission computed tomography (SPECT), and many others. Further, rapid expansion of artificial intelligence (AI) that has revolutionized several aspects of medical imaging is also poised to accelerate advances in theranostics.

This JMI special section welcomes original research papers on theranostics agents, medical imaging methods for theranostics, computational paradigms for dosimetry, dose-response studies, clinical outcomes, applications of artificial intelligence to theranostics, and more. We also welcome high-quality submissions from work presented at top conferences, such as SNMMI, EANM, AAPM, MICCAI, SPIE MI, ISBI, and others.

Topics of interest include, but are not limited to, the following:

  • Novel radionuclides in theranostics
  • Emerging imaging technologies in theranostics
  • Novel theranostics schemas under development
  • Imaging biomarkers for tumor characterization
  • Methods to identify therapeutic or diagnostic agents
  • Prediction of tumor grade and metastatic potential
  • Pre-treatment and post-treatment dosimetry in theranostics
  • Theranostics methods for cancer prognosis and monitoring
  • Multi-modal data modeling methods using imaging, lab data, and health record data
  • The role of theranostics in multimodality oncologic care including sequencing and combining therapies
  • Theranostics practical aspects in nuclear medicine clinic

Manuscripts should conform to the JMI author guidelineshttp://spie.org/JMIauthorinfo. 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.

Theranostics; image courtesy of S.C. Kappadath and ChatGPT
Published Special Sections

Digital Tomosynthesis: Past, Present, and Future (2025, in progress)
Editors: Stephen Glick, John M. Sabol, Andrew Maidment, Ingrid Reiser, and Mitch Goodsitt

Photon-counting: Detectors and Applications (2024, in progress)
Editors: Mini Das and Patrick J. La Riviere

AR/VR in Medical Imaging (November/December 2024; in progress)
Editors: Ryan Beams, Bruce Daniel, and Raj Shekhar

Global Health, Equity, Bias, and Diversity in AI in Medical Imaging (2022 - 2023)
Editors: Judy W. Gichoya, Rui C. Sá, Ronald M. Summers, and Heather Whitney

Informatics and Imaging Data Management (November/December 2023)
Editors: Katherine P. Andriole, Susan Astley, Elizabeth Krupinski, and Thomas Deserno

Artificial Intelligence in Medical Imaging for Clinical Practice (September/October 2023)
Editors: Claudia Mello-Thoms, Karen Drukker, Sian Taylor-Phillips, Khan Iftekharuddin, and Marios Gavrielides

Special Issue on Advances in Breast Imaging
(2023)
Editors: Hilde Bosmans, Alistair Mackenzie, Nicholas Marshall, Robert Marti, Martin P. Tornai, and Reyer Zwiggelaar

Special Issue on Medical Image Perception and Observer Performance (2023)
Editors: Elizabeth A. Krupinski, Asli Kumcu, and Karla Evans

Special Issue Celebrating 50 Years of SPIE Medical Imaging (2022)
Editors: Kyle Myers and Maryellen Giger

Advances in High Dimensional Medical Imaging (September/October 2022)
Editors: Ivana Išgum, Bennett A. Landman, and Tomaž Vrtovec

Hard X-Ray Tomography with Micrometer Resolution (May/June 2022)
Editors: Bert Müller, Stuart R. Stock, Ge Wang, and Jovan Brankov

COVID Medical Imaging Research (2021)
Editor: Maryellen Giger

X-Ray Computed Tomography at 50 (September/October 2021)
Editors: Norbert J. Pelc, Rebecca Fahrig, and Patrick J. La Riviere

2D and 3D Imaging: Perspectives in Human and Model Oberver Performance (September/October 2020, July/August 2021)
Editors: Claudia Mello-Thoms, Craig K. Abbey, and Elizabeth A. Krupinski

Radiogenomics in Prognosis and Treatment (May/June 2021)
Editors: Karen Drukker, Despina Kontos, and Hui Li

Virtual Clinical Trials (July/August 2020)
Editors: Ehsan Samei, Paul Kinehan, Robert M. Nishikawa, and Andrew Maidment

Interventional and Surgical Data Science (May/June 2020)
Editors: Amber Simpson and Michael Miga

Three-Dimensional Image Reconstruction in Nuclear Medicine, PET, and CT (May/June 2020)
Editors: Scott D. Metzler, Samuel Matej, and J. Webster Stayman

Medical Image Perception and Observer Performance (March/April 2020)
Editors: William F. Auffermann, Trafton Drew, and Elizabeth A. Krupinski

Evaluation Methodologies for Clinical AI (January/February 2020)
Editors: Susan M. Astley, Weijie Chen, Kyle J. Myers, and Robert M. Nishikawa

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

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

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

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

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

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

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

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

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

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

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

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

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

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