• Terrain visualization

  • Stereoscopic vision

  • Medical imaging

  • Augmented reality

  • LIDAR point cloud classification

  • Mobile devices development

  • Motion analysis

  • Emergency management systems

  • Remote sensing

Accepted paper in IEEE-GRSL
Tuesday, 02 February 2021 21:06

The paper,"Performance of speckle filters for COSMO-SkyMed images from the Brazilian Amazon", by Tahisa Kuck (Instituto de Estudos Avançados,, Sao Paulo, Brazil), Luis Gomez (CTIM, Universidad de Las Palmas de Gran Canaria, Edson E. Sano (Embrapa Cerrados, Brasilia, Bazil), Polyanna da C. Bispo (Department of Geography, School of Environment, Education and Development, University of Manchester, Oxford, UK) and Douglas D...

Accepted paper in IEEE-Access
Thursday, 08 October 2020 19:40

The paper, "Anisotropic Weighted KS-NLM Filter for Noise Reduction in MRI", by, B. Kanoun, M. Ambrosanio, F. Baselice, G. Ferraioli, V. Pascazio and L. Gómez, has been accepted for publication in the Journal IEEE-Access (DOI: 10.1109/ACCESS.2020.3029297).This paper is the result of the three months research stay by B...

Accepted paper in IEEE-JSTARS
Monday, 24 August 2020 10:26

The paper, "A Badging System for Reproducibility and Replicability in Remote Sensing Research", by Alejandro C. Frery (LaCCAN—Laboratório de Computação Científica e Análise Numérica, Universidade Federal de Alagoas, Maceió, Brazil) , Luis Gomez (CTIM, Universidad de Las Palmas de Gran Canaria, Las Palmas de Gran Canaria, Spain) and Atonio M...

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.

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