Special Issue "Biomedical Imaging and Visualization"
A special issue of Informatics (ISSN 2227-9709).
Deadline for manuscript submissions: 31 March 2014
Prof. Dr. Luc Bidaut
c/o Clinical Research Centre (CRC), James Arrott Drive, Ninewells Hospital & Medical School, Dundee, DD1 9SY, Scotland, UK
Phone: +44 1382 383 431
Fax: +44 1382 383 611
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
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
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.
- biomedical imaging
Title: Artery Segmentation in Ultrasound Images Based on an Evolutionary Scheme
Authors: Pablo Guzman 1,*, Rafael Ros 2,*, Eduardo Ros 1
Affiliation: 1Department of Computer Architecture and Technology. ETSI Informática y de Telecomunicación. CITIC-UGR, University of Granada, Spain; 2Hospital Universitario San Cecilio, Servicio de Angiología y Cirugía Vascular. Granada; E-Mail: firstname.lastname@example.org
Abstract: Segmentation in UltraSound 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 we propose a solution based on ellipse fitting motivated by natural artery geometry. To optimize the parameters that define such ellipse, we make use of an evolutionary algorithm. We demonstrate that the method can be solved in a reasonable time making intensive use of GPGPU (General Processing GPU) where we obtain an excellent increase of computation performance (up to 54 times faster than the parallel CPU implementation). The proposed approach is compared with other artery segmentation methods in UltraSound images obtaining very promising results. Furthermore, the proposed approach is parameter free and does not require initialization estimation close to the final solution.
Last update: 27 November 2013