Institute of Computer Science at FORTH

Irákleion, Greece

Institute of Computer Science at FORTH

Irákleion, Greece
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Khan Z.,University of Oulu | Lehtomaki J.J.,Institute of Computer Science at FORTH | Iellamo S.I.,Institute of Computer Science at FORTH | Vuohtoniemi R.,University of Manitoba | And 2 more authors.
IEEE Communications Magazine | Year: 2017

To address the challenge of more spectrum for IoT connectivity, this article proposes an SA framework with rotating radars. The proposed framework is based on the results of our measurement campaign in which we measured spectrum usage patterns and signal characteristics of three different ground-based fixed rotating radar systems near Oulu, Finland. In our work, we review different IoT protocols and their use of licensed or unlicensed spectrum. We make the case that IoT systems generate much data that cannot be accommodated with licensed/unlicensed spectrum, which already suffer from congestion. We identify the suitability of shared access between different rotating radars and IoT networks. We then present a zone-based SA framework in rotating radar spectrum for the operators providing IoT services, highlight its benefits, and also specify challenges in its implementation. To fully develop the considered zone-based SA method that ensures coexistence of IoT devices with no harmful interference to the rotating radars, we propose an REM-enabled architecture for the SA. The proposed architecture provides principles and rules for using the SA for the IoT, and it does not require modifications in the incumbent radar systems. © 1979-2012 IEEE.


Sfakianakis S.,Institute of Computer Science at FORTH | Sakkalis V.,Institute of Computer Science at FORTH | Marias K.,Institute of Computer Science at FORTH | Stamatakos G.,National Technical University of Athens | And 3 more authors.
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2012

The TUMOR project aims at developing a European clinically oriented semantic-layered cancer digital model repository from existing EU projects that will be interoperable with the US grid-enabled semantic-layered digital model repository platform at CViT.org (Center for the Development of a Virtual Tumor, Massachusetts General Hospital (MGH), Boston, USA) which is NIH/NCI-caGRID compatible. In this paper we describe the modular and federated architecture of TUMOR that effectively addresses model integration, interoperability, and security related issues. © 2012 IEEE.


Sakkalis V.,Institute of Computer Science at FORTH
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2010

This paper investigates the applicability of multilevel macroscopic models for simulating solid tumor growth in the invasive glioblastoma multiforme (GBM) case. The continuum case approach tumor model based on the diffusion reaction equation is evaluated on a pre-segmented tomographic atlas where all tissue properties are known a priori. The atlas is further registered on a real clinical case where the tumor invasion status is gauged in two successive points in time. Based on the latter, the model attempts to fully replicate tumor growth taking into account tissue based properties as identified from the atlas template. The whole process is performed on a clinical platform specially designed to facilitate precise identification and delineation of tumors of large number of 3D tomographic datasets by an expert clinician. The promising results presented encourage the potential clinical applicability of the proposed model in the glioma case and identify crucial points and direction of further model refinement and research.


Muller S.,Saarland University | David R.,Saarland University | Marias K.,Institute of Computer Science at FORTH | Graf N.,Saarland University
Cancer Informatics | Year: 2015

The objective of this study is to assess standardized histograms of signal intensities of T2-weighted magnetic resonance image (MRI) modality before and after preoperative chemotherapy for nephroblastoma (Wilms’ tumor). All analyzed patients are enrolled in the International Society of Paediatric Oncology (SIOP) 2001/GPOH trial.1 The question to be answered is whether the comparison of the histograms can add new knowledge by comparing them with the histology of the tumor after preoperative chemotherapy. Twenty-three unilateral nephroblastoma cases were analyzed. All patients were examined by MRI before and after preoperative chemotherapy treatment. T2 modalities of the MRIs were selected, and histogram changes were compared to histopathological data available after surgery. Of the 23 tumors, 22 decreased in volume following chemotherapy (median −57.99%; range 15.65 to −90.82%). The preliminary results suggest that standardized histograms of signal intensities of T2 MRI in nephroblastoma is not predicting his-topathological diagnostic information and has no implications for the clinical assessment for further chemotherapy. © the authors, publisher and licensee Libertas Academica Limited.


Sakkalis V.,Institute of Computer Science at FORTH | Manikis G.C.,Institute of Computer Science at FORTH | Papanikolaou N.,N. Papanikolaou and Associates STEP C | Karatzanis I.,Institute of Computer Science at FORTH | Marias K.,Institute of Computer Science at FORTH
Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS | Year: 2012

Advanced MRI techniques including diffusion and perfusion weighted imaging, has the potential to provide early surrogate biomarkers to detect, characterize and assess treatment response of tumors. However, the widely accepted Response Evaluation Criteria in Solid Tumors (RECIST) are still considered as the gold standard for the evaluation of treatment response in solid tumors, even if according to recent studies RECIST seem to disregard the extent of necrosis, which is the target of all effective locoregional therapies. This is partly due to the fact that measurements of tumor size aren't the best criterion for assessing actual early response. On the other hand, more sophisticated techniques such as the Apparent Diffusion Coefficient (ADC) and perfusion parameters are usually processed manually and evaluated independently using commercial CAD software, not widely available. In this paper we present an open access extensible software platform providing both diffusion and perfusion analysis in a single, user friendly environment that allows the radiologist to easily and objectively evaluate tumor response to therapy. © 2012 IEEE.


Siris V.A.,Athens University of Economics and Business | Tragos E.Z.,Institute of Computer Science at FORTH | Petroulakis N.E.,Institute of Computer Science at FORTH
IEEE Communications Magazine | Year: 2012

Wireless mesh networks comprise nodes with multiple radio interfaces, and can provide lowcost high-speed Internet access or connectivity for data transfer. In this article we report our experiences and investigations with an experimental metropolitan multiradio mesh network that covers an area of approximately 60 km2 in the city of Heraklion, Crete. We present the design and deployment of the network, experiments to quantify the network's performance, and an application that runs on top of it and exploits it's low-cost wide-area connectivity. The metropolitan network consists of 16 nodes, among which six are core nodes, each with up to four 802.11a wireless interfaces and an additional wireless interface for management and monitoring. The distance between core mesh nodes varies from 1.6 to 5 km, and the mesh network contains two gateways that connect it to a wired network. Our performance experiments involve rate, power, and channel control for long-distance metropolitan links, and include investigations of the timescales for the operation for these mechanisms. Finally, we present a system for continuous online electromagnetic field monitoring and spectrum sensing, which utilizes the metropolitan mesh network for collecting widearea measurements from low-cost EMF measurement devices. © 2012 IEEE.


Sfakianakis S.,Institute of Computer Science at FORTH
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

The TUMOR project aims at developing a European clinically oriented semantic-layered cancer digital model repository from existing EU projects that will be interoperable with the US grid-enabled semantic-layered digital model repository platform at CViT.org (Center for the Development of a Virtual Tumor, Massachusetts General Hospital (MGH), Boston, USA) which is NIH/NCI-caGRID compatible. In this paper we describe the modular and federated architecture of TUMOR that effectively addresses model integration, interoperability, and security related issues.


PubMed | Institute of Computer Science at FORTH
Type: Journal Article | Journal: Interface focus | Year: 2012

The challenge of modelling cancer presents a major opportunity to improve our ability to reduce mortality from malignant neoplasms, improve treatments and meet the demands associated with the individualization of care needs. This is the central motivation behind the ContraCancrum project. By developing integrated multi-scale cancer models, ContraCancrum is expected to contribute to the advancement of in silico oncology through the optimization of cancer treatment in the patient-individualized context by simulating the response to various therapeutic regimens. The aim of the present paper is to describe a novel paradigm for designing clinically driven multi-scale cancer modelling by bringing together basic science and information technology modules. In addition, the integration of the multi-scale tumour modelling components has led to novel concepts of personalized clinical decision support in the context of predictive oncology, as is also discussed in the paper. Since clinical adaptation is an inelastic prerequisite, a long-term clinical adaptation procedure of the models has been initiated for two tumour types, namely non-small cell lung cancer and glioblastoma multiforme; its current status is briefly summarized.


Sakkalis V.,Institute of Computer Science at FORTH
Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Conference | Year: 2012

Advanced MRI techniques including diffusion and perfusion weighted imaging, has the potential to provide early surrogate biomarkers to detect, characterize and assess treatment response of tumors. However, the widely accepted Response Evaluation Criteria in Solid Tumors (RECIST) are still considered as the gold standard for the evaluation of treatment response in solid tumors, even if according to recent studies RECIST seem to disregard the extent of necrosis, which is the target of all effective locoregional therapies. This is partly due to the fact that measurements of tumor size aren't the best criterion for assessing actual early response. On the other hand, more sophisticated techniques such as the Apparent Diffusion Coefficient (ADC) and perfusion parameters are usually processed manually and evaluated independently using commercial CAD software, not widely available. In this paper we present an open access extensible software platform providing both diffusion and perfusion analysis in a single, user friendly environment that allows the radiologist to easily and objectively evaluate tumor response to therapy.


PubMed | Institute of Computer Science at FORTH
Type: | Journal: Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference | Year: 2010

This paper investigates the applicability of multilevel macroscopic models for simulating solid tumor growth in the invasive glioblastoma multiforme (GBM) case. The continuum case approach tumor model based on the diffusion reaction equation is evaluated on a pre-segmented tomographic atlas where all tissue properties are known a priori. The atlas is further registered on a real clinical case where the tumor invasion status is gauged in two successive points in time. Based on the latter, the model attempts to fully replicate tumor growth taking into account tissue based properties as identified from the atlas template. The whole process is performed on a clinical platform specially designed to facilitate precise identification and delineation of tumors of large number of 3D tomographic datasets by an expert clinician. The promising results presented encourage the potential clinical applicability of the proposed model in the glioma case and identify crucial points and direction of further model refinement and research.

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