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Dear Colleagues,
We are delighted to welcome submissions for the upcoming Special Issue on Image-based structural and functional tissue characterisation for personalised modelling, to be published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. We believe this Special Issue will be of significant interest to many in this list. Please, see below for further details, and feel free to contact me with any queries.
Best wishes,
Zeike Taylor
Department of Mechanical Engineering
CISTIB Centre for Computational Imaging & Simulation Technologies in Biomedicine
INSIGNEO Institute for in silico Medicine
The University of Sheffield
Mappin Street, Sheffield, S1 3JD, UK
T: +44 (0)114 2227719
E: z.a.taylor@sheffield.ac.uk
Rationale
Initiatives like the Virtual Physiological Human and the IUPS Physiome Project are indicative of worldwide efforts to develop a comprehensive and integrative approach to modelling human physiology, bridging spatial and temporal scales, and bringing together disparate physical conceptions of the human organism. Such an achievement is fundamental to the vision of personalised in silico medicine, in which patient-specific models, images and other signals are combined to produce a so-called digital patient, upon which simulation-based prognoses and predictions of outcomes of therapeutic courses may be performed. Imaging and modelling are central and symbiotic tools: models can augment and enhance observations from images and other signals, which generally are sparse and incomplete, to build a fuller picture of an individual’s physiology and disease state, both presently and in the future. That is, they potentially reveal hidden or additional aspects of patient physiology not directly observable or inferable from the signals themselves: so-called model-based imaging. In addition, images provide the central means of non-invasively personalising patient models, for example in terms of anatomical geometry and structure at different scales, physical and chemical constitution and corresponding model parameters, and boundary conditions, such as motion, flow and metabolic activity: so-called image-based modelling.
This special issue is concerned with developments in image-based modelling, and in particular with image-based methods for biophysical and physiological characterisation of tissues. These might relate to any structural or functional properties at any biological level of organisation, and imply a range as wide as that of the models that incorporate them. Moreover, besides their application in model personalisation, such methods may also be clinically useful in their own right as biomarkers of pathology, as in the case of elastography, for example. While integrative computational modelling offers the prospect of a new paradigm in medicine, reliable and efficient methods for personalising these models for individual subjects in vivo are essential for realising this vision and translating the new technologies to the clinic.
Suggested Topics
The following list is indicative and intended in no way to be exclusive:
• Elastography: magnetic resonance-based, ultrasound-based, poro-elastography
• Image-based tissue electrical and thermal conductivity estimation
• Image-based estimation of bio-fluid and flow properties
• Image-based assessment of tissue permeability and mass transport properties
• Image-based estimation of tissue acoustic properties
• Image-based estimation of tissue biochemical and metabolic characteristics
• Applications to pathological tissues, biomarker development, diagnostics and therapeutic planning/monitoring
• Novel devices for non-destructive in-vivo characterisation of tissues
• Novel imaging modalities and techniques for biophysical characterisation
• Fusion of multi-modal and/or multi-scale data for tissue characterisation
• Microscopy-based methods for characterisation of tissue microstructure and function
• Inverse and filter-based methods for parameter identification
• Experimental and computational developments
• Statistical and population-based methods.
Submission Instructions
Full details may be found here: http://explore.tandfonline.com/cfp/est/tciv
We are seeking high quality research papers for this special issue and will welcome full-paper submissions. Authors should submit their manuscripts following the regular journal editorial policies and selecting the special issue on Image-based structural and functional tissue characterisation for personalised modelling during the submission process. Authors intending to submit articles are encouraged to discuss their submissions with the Guest Editors to determine suitability for this special issue.
Submission of manuscripts: 1 June 2014
Acceptance/rejection notification: 1 September 2014
Revised manuscripts due: 1 November 2014
Final acceptance: 1 January 2015
Publication: 1 May 2015
Editorial Information
Guest Editor: Zeike A. Taylor, University of Sheffield (z.a.taylor@sheffield.ac.uk)
Guest Editor: Alejandro F. Frangi, University of Sheffield (a.frangi@sheffield.ac.uk )
Guest Editor: Sebastian Kozerke, University and ETH Zurich (kozerke@biomed.ee.ethz.ch)
Guest Editor: Michael I. Miga, Vanderbilt University (michael.i.miga@vanderbilt.edu)
Guest Editor: Frank B Sachse , University of Utah (frank.sachse@utah.edu)
We are delighted to welcome submissions for the upcoming Special Issue on Image-based structural and functional tissue characterisation for personalised modelling, to be published in Computer Methods in Biomechanics and Biomedical Engineering: Imaging & Visualization. We believe this Special Issue will be of significant interest to many in this list. Please, see below for further details, and feel free to contact me with any queries.
Best wishes,
Zeike Taylor
Department of Mechanical Engineering
CISTIB Centre for Computational Imaging & Simulation Technologies in Biomedicine
INSIGNEO Institute for in silico Medicine
The University of Sheffield
Mappin Street, Sheffield, S1 3JD, UK
T: +44 (0)114 2227719
E: z.a.taylor@sheffield.ac.uk
Rationale
Initiatives like the Virtual Physiological Human and the IUPS Physiome Project are indicative of worldwide efforts to develop a comprehensive and integrative approach to modelling human physiology, bridging spatial and temporal scales, and bringing together disparate physical conceptions of the human organism. Such an achievement is fundamental to the vision of personalised in silico medicine, in which patient-specific models, images and other signals are combined to produce a so-called digital patient, upon which simulation-based prognoses and predictions of outcomes of therapeutic courses may be performed. Imaging and modelling are central and symbiotic tools: models can augment and enhance observations from images and other signals, which generally are sparse and incomplete, to build a fuller picture of an individual’s physiology and disease state, both presently and in the future. That is, they potentially reveal hidden or additional aspects of patient physiology not directly observable or inferable from the signals themselves: so-called model-based imaging. In addition, images provide the central means of non-invasively personalising patient models, for example in terms of anatomical geometry and structure at different scales, physical and chemical constitution and corresponding model parameters, and boundary conditions, such as motion, flow and metabolic activity: so-called image-based modelling.
This special issue is concerned with developments in image-based modelling, and in particular with image-based methods for biophysical and physiological characterisation of tissues. These might relate to any structural or functional properties at any biological level of organisation, and imply a range as wide as that of the models that incorporate them. Moreover, besides their application in model personalisation, such methods may also be clinically useful in their own right as biomarkers of pathology, as in the case of elastography, for example. While integrative computational modelling offers the prospect of a new paradigm in medicine, reliable and efficient methods for personalising these models for individual subjects in vivo are essential for realising this vision and translating the new technologies to the clinic.
Suggested Topics
The following list is indicative and intended in no way to be exclusive:
• Elastography: magnetic resonance-based, ultrasound-based, poro-elastography
• Image-based tissue electrical and thermal conductivity estimation
• Image-based estimation of bio-fluid and flow properties
• Image-based assessment of tissue permeability and mass transport properties
• Image-based estimation of tissue acoustic properties
• Image-based estimation of tissue biochemical and metabolic characteristics
• Applications to pathological tissues, biomarker development, diagnostics and therapeutic planning/monitoring
• Novel devices for non-destructive in-vivo characterisation of tissues
• Novel imaging modalities and techniques for biophysical characterisation
• Fusion of multi-modal and/or multi-scale data for tissue characterisation
• Microscopy-based methods for characterisation of tissue microstructure and function
• Inverse and filter-based methods for parameter identification
• Experimental and computational developments
• Statistical and population-based methods.
Submission Instructions
Full details may be found here: http://explore.tandfonline.com/cfp/est/tciv
We are seeking high quality research papers for this special issue and will welcome full-paper submissions. Authors should submit their manuscripts following the regular journal editorial policies and selecting the special issue on Image-based structural and functional tissue characterisation for personalised modelling during the submission process. Authors intending to submit articles are encouraged to discuss their submissions with the Guest Editors to determine suitability for this special issue.
Submission of manuscripts: 1 June 2014
Acceptance/rejection notification: 1 September 2014
Revised manuscripts due: 1 November 2014
Final acceptance: 1 January 2015
Publication: 1 May 2015
Editorial Information
Guest Editor: Zeike A. Taylor, University of Sheffield (z.a.taylor@sheffield.ac.uk)
Guest Editor: Alejandro F. Frangi, University of Sheffield (a.frangi@sheffield.ac.uk )
Guest Editor: Sebastian Kozerke, University and ETH Zurich (kozerke@biomed.ee.ethz.ch)
Guest Editor: Michael I. Miga, Vanderbilt University (michael.i.miga@vanderbilt.edu)
Guest Editor: Frank B Sachse , University of Utah (frank.sachse@utah.edu)