Special Issue "Biomedical Imaging and Visualization"

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A special issue of Informatics (ISSN 2227-9709).

Deadline for manuscript submissions: closed (30 October 2015)

Special Issue Editor

Guest Editor
Prof. Dr. Luc Bidaut (Website)

Clinical Research Imaging Facility (CRIF), c/o Clinical Research Centre (CRC), James Arrott Drive, Ninewells Hospital & Medical School, Dundee, DD1 9SY, Scotland, UK
Phone: +44 1382 383 431
Interests: advanced biomedical imaging (modalities, processing and exploitation) and all ancillaries and applications thereof; preclinical imaging; 3D imaging, processing and visualisation; multimodality imaging, processing and visualisation; image-guided biomedical applications (diagnosis, therapy planning, monitoring, follow-up); virtual and augmented reality; high-performance computing and visualisation; telemedicine; biomedical image archival

Special Issue Information

Dear Colleagues,

Biomedical Imaging and Visualization are intrinsic and ever more critical components of most modern biological and medical research and applications. While the technical scope includes detectors, complete instruments, computing (from algorithms to models) and integrative paradigms, the applications span multiple scales (from single cells to live systems), species (from animals to humans), characteristics (from morphology to function), and of course diseases or treatments thereof (e.g., neuro-, cardio-, vascular, skeletal, diabetes, cancer). Even though the overarching umbrella of this Special Issue is "Informatics" (the journal), its intended scope is not to be limited to only one discipline, modality, application, scale and species, which thus offers an ideal setting for computing-aware material that may cross disciplines and applications boundaries and techniques.

Of special relevance in such a context are all biomedical applications of advanced imaging: multidimensional (at any scale, including new imaging equipment and paradigms based on various physical principles) and multimodality/multisensor approaches (e.g., registration, fusion and visualization); disease and treatment characterization (e.g., through various related metrics); image-guidance and navigation (incl., robotics); planning, monitoring and follow-up of treatment; modeling and simulation (e.g., for improved planning and delivery); visualization of complex data sets and analyses (e.g., for improved diagnosis or therapy management); etc.

Prof. Dr. Luc Bidaut
Guest Editor

Submission

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. Papers will be published continuously (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are refereed through a peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Informatics is an international peer-reviewed Open Access quarterly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. For the first couple of issues the Article Processing Charge (APC) will be waived for well-prepared manuscripts. English correction and/or formatting fees of 250 CHF (Swiss Francs) will be charged in certain cases for those articles accepted for publication that require extensive additional formatting and/or English corrections.

Keywords

  • biomedical imaging
  • visualization
  • post-processing
  • segmentation
  • registration
  • multidimensional
  • multimodality
  • preclinical
  • clinical
  • reconstruction
  • simulation
  • modeling

Published Papers (3 papers)

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Research

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Open AccessArticle How Using Dedicated Software Can Improve RECIST Readings
Informatics 2014, 1(2), 160-173; doi:10.3390/informatics1020160
Received: 31 March 2014 / Revised: 22 August 2014 / Accepted: 1 September 2014 / Published: 8 September 2014
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Abstract
Decision support tools exist for oncologic follow up. Their main interest is to help physicians improve their oncologic readings but this theoretical benefit has to be quantified by concrete evidence. The purpose of the study was to evaluate and quantify the impact [...] Read more.
Decision support tools exist for oncologic follow up. Their main interest is to help physicians improve their oncologic readings but this theoretical benefit has to be quantified by concrete evidence. The purpose of the study was to evaluate and quantify the impact of using dedicated software on RECIST readings. A comparison was made between RECIST readings without dedicated application vs. readings using dedicated software (Myrian® XL-Onco, Intrasense, France) with specific functionalities such as 3D elastic target matching and automated calculation of tumoral response. A retrospective database of 40 patients who underwent a CT scan follow up was used (thoracic/abdominal lesions). The reading panel was composed of two radiologists. Reading times, intra/inter-operator reproducibility of measurements and RECIST response misclassifications were evaluated. On average, reading time was reduced by 49.7% using dedicated software. A more important saving was observed for lung lesions evaluations (63.4% vs. 36.1% for hepatic targets). Inter and intra-operator reproducibility of measurements was excellent for both reading methods. Using dedicated software prevented misclassifications on 10 readings out of 120 (eight due to calculation errors). The use of dedicated oncology software optimises RECIST evaluation by decreasing reading times significantly and avoiding response misclassifications due to manual calculation errors or approximations. Full article
(This article belongs to the Special Issue Biomedical Imaging and Visualization)
Figures

Open AccessArticle Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme
Informatics 2014, 1(1), 52-71; doi:10.3390/informatics1010052
Received: 22 November 2013 / Revised: 16 January 2014 / Accepted: 6 February 2014 / Published: 25 February 2014
Cited by 1 | PDF Full-text (1247 KB) | HTML Full-text | XML Full-text
Abstract
Segmentation in ultrasound (US) images is a challenge in computer vision, due to the high signal noise, artifacts that produce discontinuities in the boundaries and shadows that hide part of the received signal. In this paper, a solution based on ellipse fitting [...] Read more.
Segmentation in ultrasound (US) images is a challenge in computer vision, due to the high signal noise, artifacts that produce discontinuities in the boundaries and shadows that hide part of the received signal. In this paper, a solution based on ellipse fitting motivated by natural artery geometry will be proposed. To optimize the parameters that define such an ellipse, a strategy based on an evolutionary algorithm was adopted. The paper will also demonstrate that the method can be solved in a reasonable amount of time, making intensive GPGPU (general graphics processing unit, GPU, processing) where excellent computing performance gain is obtained (up to 54 times faster than the parallel CPU implementation). The proposed approach is compared with other artery segmentation methods in US images, obtaining very promising results. Furthermore, the proposed approach is parameter free and does not require any initialization estimation close to the final solution. Full article
(This article belongs to the Special Issue Biomedical Imaging and Visualization)

Review

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Open AccessReview Molecular Imaging of Bacterial Infections in vivo: The Discrimination between Infection and Inflammation
Informatics 2014, 1(1), 72-99; doi:10.3390/informatics1010072
Received: 18 March 2014 / Revised: 6 May 2014 / Accepted: 13 May 2014 / Published: 30 May 2014
Cited by 4 | PDF Full-text (431 KB) | HTML Full-text | XML Full-text
Abstract
Molecular imaging by definition is the visualization of molecular and cellular processes within a given system. The modalities and reagents described here represent a diverse array spanning both pre-clinical and clinical applications. Innovations in probe design and technologies would greatly benefit therapeutic [...] Read more.
Molecular imaging by definition is the visualization of molecular and cellular processes within a given system. The modalities and reagents described here represent a diverse array spanning both pre-clinical and clinical applications. Innovations in probe design and technologies would greatly benefit therapeutic outcomes by enhancing diagnostic accuracy and assessment of acute therapy. Opportunistic pathogens continue to pose a worldwide threat, despite advancements in treatment strategies, which highlights the continued need for improved diagnostics. In this review, we present a summary of the current clinical protocol for the imaging of a suspected infection, methods currently in development to optimize this imaging process, and finally, insight into endocarditis as a model of infectious disease in immediate need of improved diagnostic methods. Full article
(This article belongs to the Special Issue Biomedical Imaging and Visualization)

Submitted Papers


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