• Remote sensing

  • Augmented reality

  • Terrain visualization

  • LIDAR point cloud classification

  • Motion analysis

  • Medical imaging

  • Emergency management systems

  • Stereoscopic vision

  • Mobile devices development

Remote Sensing Special Issue
Wednesday, 15 July 2020 12:28

A call for papers to contribute to a Remote Sensing Special Issue, "Emerging Techniques and Applications of Polarimetric SAR" is now open.Remote Sensing -one of the top JCR Journals in remote sensing- has a 5-year JCR impact factor of 4.509 and an average turnaround time close to 30 days.Guest Editors for this Special Issue are:Dr...

 
New article published in the journal Medical & Biological Engineering & Computing (MBEC)
Thursday, 20 February 2020 20:32

The article "Automatic detection of anatomical landmarks of the aorta in CTA images", has been published in the journal Medical & Biological Engineering & Computing (MBEC) from Springer Nature. MBEC is an official journal of the International Federation of Medical and Biological Engineering (IFMBE). The work described in this paper is the result of a collaboration between researchers from the University of Santiago de Compostela and from CTIM, R&D Center belonging to the University of Las Palmas de Gran Canaria.In this article, the authors demonstrate the feasibility of a fully automated technology for the accurate detection and identification of several anatomical reference points (landmarks), commonly used in intravascular imaging. This technology uses two different approaches, specially designed for the detection of the aortic root and supra-aortic and visceral branches. In order to adjust the parameters of the developed algorithms, a total of 33 computed tomography scans with different types of pathologies were selected. Furthermore, a total of 30 independently selected computed tomography scans were used to assess their performance. Accuracy was evaluated by comparing the locations of reference points manually marked by human experts with those that were automatically detected. For supra-aortic and visceral branches detection, average values of 91.8 % for recall and 98.8 % for precision were obtained. For aortic root detection, the average difference between the positions marked by the experts and those detected by the computer was 5.7 ± 7.3 mm. Finally, diameters and lengths of the aorta were measured at different locations related to the extracted landmarks. Those measurements agreed with the values reported by the literature.For more information about this article, please visit the following link.

 
Machine Learning Talk at CTIM
Thursday, 12 December 2019 12:32

In the context of the program Erasmus professional graduates (EHES - European Higher Education Area), Dr. Pedro Henríquez Castellano will give a talk at the Imaging Technology Center. In this presentation, Dr. Henríquez will address the Random Forests technique, and how to configure this machine learning method to perform object detection in 2D and 3D images...

 
New Approaches to Denoising Magnetic Resonance Images with Nonlocal Means Filters
Tuesday, 10 December 2019 13:44

On Friday 13th, Bilel Kanoun will give a talk regarding MRI denoising. In this talk, state-of of the art of some most relevant Works in the MRI denoising area will be addressed. Then, the main ideas of new filtering approaches will be illustrated and also future perspectives will be considered.Bilel Kanoun is a Ph...

 
Guest Editor at Special Issues in Journal of Medical Imaging and Health Informatics
Monday, 09 December 2019 09:17

Three Special Issues have been published on Journal of Medical Imaging and Health Informatics. The earlier two issues have been indexed by SCI successfully, and the last issue will be indexed later. Dr. Luis Gomez was the Head Editor of the three Issues, and Dr...

 
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