Ignacio Blanquer Espert

SLA-driven dynamic cloud resource management

As the size and complexity of Cloud systems increases, the manual management of these solutions becomes a challenging issue as more personnel, resources and expertise are needed. Service Level Agreement (SLA)-aware autonomic cloud solutions enable managing large scale infrastructure management meanwhile supporting multiple dynamic requirement from users. This paper contributes to these topics by the introduction of Cloudcompaas, a SLA-aware PaaS Cloud platform that manages the complete resource lifecycle. This platform features an extension of the SLA specification WSAgreement, tailored to the specific needs of Cloud Computing. In particular, Cloudcompaas enables Cloud providers with a generic SLA model to deal with higher-level metrics, closer to end-user perception, and with flexible composition of the requirements of multiple actors in the computational scene. Moreover, Cloudcompaas provides a framework for general Cloud computing applications that could be dynamically adapted to correct the QoS violations by using the elasticity features of Cloud infrastructures. The effectiveness of this solution is demonstrated in this paper through a simulation that considers several realistic workload profiles, where Cloudcompaas achieve minimum cost and maximum efficiency, under highly heterogeneous utilization patterns.

Content-based organisation of virtual repositories of DICOM objects

The integration of multi-centre medical image data to create knowledge repositories for research and training activities has been an aim targeted since long ago. This paper presents an environment to share, to process and to organise medical imaging data according to a structured framework in which the image reports play a key role. This environment has been validated on a clinical environment, facing problems such as firewalls and security restrictions, in the frame of the CVIMO (Valencian Cyberinfrastructure of Medical Imaging in Oncology) project. The environment uses a middleware called TRENCADIS (Towards a Grid Environment for Processing and Sharing DICOM Objects) that provides users with the management of multiple administrative domains, data encryption and decryption on the fly and semantic indexation of images. Data is structured into four levels: Global data available, virtual federated storages of studies shared across a vertical domain, subsets for projects or experiments on the virtual storage and individual searches on these subsets. This structure of levels gives the needed flexibility for organising authorisation, and hides data that are not relevant for a given experiment. The main components and interactions are shown in the document, outlining the workflows and explaining the different approaches considered, including the protocols used and the difficulties met.

Enabling e-science applications on the cloud with COMPSs

COMP Superscalar (COMPSs) is a programming framework that provides an easy-to-use programming model and a runtime to ease the development of applications for distributed environments. Thanks to its modular architecture COMPSs can use a wide range of computational infrastructures providing a uniform interface for job submission and file transfer operations through adapters for different middlewares. In the context of the VENUS-C project the COMPSs framework has been extended through the development of a programming model enactment service that allows researcher to transparently port and execute scientific applications in the Cloud. This paper presents the implementation of a bioinformatics workflow (using BLAST as core program), the porting to the COMPSs framework and its deployment on the VENUS-C platform. The proposed approach has been evaluated on a Cloud testbed using virtual machines managed by EMOTIVE Cloud and compared to a similar approach on the Azure platform and to other implementations on HPC infrastructures.

An OGSA Middleware for Managing Medical Images using Ontologies

This article presents a Middleware based on Grid Technologies that addresses the problem of sharing, transferring and processing DICOM medical images in a distributed environment using an ontological schema to create virtual communities and to define common targets. It defines a distributed storage that builds-up virtual repositories integrating different individual image repositories providing global searching, progressive transmission, automatic encryption and pseudo-anonimisation and a link to remote processing services. Users from a Virtual Organisation can share the cases that are relevant for their communities or research areas, epidemiological studies or even deeper analysis of complex individual cases.Software architecture has been defined for solving the problems that has been exposed before. Briefly, the architecture comprises five layers (from the more physical layer to the more logical layer) based in Grid Thecnologies. The lowest level layers (Core Middleware Layer and Server Services sc l}ayer) are composed of Grid Services that implement the global managing of resources. The Middleware Components Layer provides a transparent view of the Grid environment and it has been the main objective of this work. Finally, the upest layer (the Application Layer) comprises the applications, and a simple application has been implemented for testing the components developed in the Components Middleware Layer.Other side-results of this work are the services developed in the Middleware Components Layer for managing DICOM images, creating virtual DICOM storages, progressive transmission, automatic encryption and pseudo-anonimisation depending on the ontologies. Other results, such as the Grid Services developed in the lowest layers, are also described in this article. Finally a brief performance analysis and several snapshots from the applications developed are shown.The performance analysis proves that the components developed in this work provide image processing applications with new possibilities for large-scale sharing, management and processing of DICOM images. The results show that the components fulfil the objectives proposed. The extensibility of the system is achieved by the use of open methods and protocols, so new components can be easily added.

A Systematic Approach for Using DICOM Structured Reports in Clinical Processes: Focus on Breast Cancer

This paper describes a methodology for redesigning the clinical processes to manage diagnosis, follow-up, and response to treatment episodes of breast cancer. This methodology includes three fundamental elements: (1) identification of similar and contrasting cases that may be of clinical relevance based upon a target study, (2) codification of reports with standard medical terminologies, and (3) linking and indexing the structured reports obtained with different techniques in a common system. The combination of these elements should lead to improvements in the clinical management of breast cancer patients. The motivation for this work is the adaptation of the clinical processes for breast cancer created by the Valencian Community health authorities to the new techniques available for data processing. To achieve this adaptation, it was necessary to design nine Digital Imaging and Communications in Medicine (DICOM) structured report templates: six diagnosis templates and three summary templates that combine reports from clinical episodes. A prototype system is also described that links the lesion to the reports. Preliminary tests of the prototype have shown that the interoperability among the report templates allows correlating parameters from different reports. Further work is in progress to improve the methodology in order that it can be applied to clinical practice.This paper describes a methodology for redesigning the clinical processes to manage diagnosis, follow-up, and response to treatment episodes of breast cancer. This methodology includes three fundamental elements: (1) identification of similar and contrasting cases that may be of clinical relevance based upon a target study, (2) codification of reports with standard medical terminologies, and (3) linking and indexing the structured reports obtained with different techniques in a common system. The combination of these elements should lead to improvements in the clinical management of breast cancer patients. The motivation for this work is the adaptation of the clinical processes for breast cancer created by the Valencian Community health authorities to the new techniques available for data processing. To achieve this adaptation, it was necessary to design nine Digital Imaging and Communications in Medicine (DICOM) structured report templates: six diagnosis templates and three summary templates that combine reports from clinical episodes. A prototype system is also described that links the lesion to the reports. Preliminary tests of the prototype have shown that the interoperability among the report templates allows correlating parameters from different reports. Further work is in progress to improve the methodology in order that it can be applied to clinical practice.

Improving knowledge management through the support of image examination and data annotation using DICOM structured reporting

An important effort has been invested on improving the image diagnosis process in different medical areas using information technologies. The field of medical imaging involves two main data types: medical imaging and reports. Developments based on the DICOM standard have demonstrated to be a convenient and widespread solution among the medical community. The main objective of this work is to design a Web application prototype that will be able to improve diagnosis and follow-on of breast cancer patients. It is based on TRENCADIS middleware, which provides a knowledge-oriented storage model composed by federated repositories of DICOM image studies and DICOM-SR medical reports. The full structure and contents of the diagnosis reports are used as metadata for indexing images. The TRENCADIS infrastructure takes full advantage of Grid technologies by deploying multi-resource grid services that enable multiple views (reports schemes) of the knowledge database. The paper presents a real deployment of such Web application prototype in the Dr. Peset Hospital providing radiologists with a tool to create, store and search diagnostic reports based on breast cancer explorations (mammography, magnetic resonance, ultrasound, pre-surgery biopsy and post-surgery biopsy), improving support for diagnostics decisions. A technical details for use cases (outlining enhanced multi-resource grid services communication and processing steps) and interactions between actors and the deployed prototype are described. As a result, information is more structured, the logic is clearer, network messages have been reduced and, in general, the system is more resistant to failures.

Accelerating the Diffusion-Weighted Imaging Biomarker in the clinical practice: comparative study.

Abstract Diffusion Weighted Imaging (DWI) methods (ADC and IVIM models) extract meaningful information about the microscopic motions of water of human tissues from MRIs. This is a non invasive method which plays an important role in the diagnosis of ischemic strokes, high grade gliomas or tumors. In the La Fe Polytechnic and University Hospital, the DWI methods aforementioned are used in clinical practice and Matlab is used as a development tool for his out of box performance and fast prototyping. However, each image takes hours to compute due to Matlab’s environment and interpreted functions. Because of this, its use in clinical practice is limited. In this paper we present three compiled versions on which different parallel paradigms based on multicore (OpenMP) and GPU (CUDA) are applied. These implementations have managed to reduce the computation time to less than one minute, therefore, it allows easing their use in daily clinical practice at a cheap acquisition cost.

Pair-End Inexact Mapping on Hybrid GPU Environments and Out-Of-Core Indexes

The authors would like to thank the Universitat Politecnica de Valencia (Spain) in the frame of the grant “High-performance tools for the alignment of genetic sequences using graphic accelerators (GPGPUs) / Herramientas de altas prestaciones para el alineamiento de secuencias geneticas mediante el uso de aceleradores graficos (GPGPUs)”, research program PAID- 06-11, code 2025.

Gpf4Med: A Large-Scale Graph Processing System Applied to the Study of Breast Cancer

Today, there is much knowledge that is not exploited from the clinical records from thousands of patients treated at different centres. In part, this is because traditional databases fail from revealing undiscovered correlations that can contribute to improve clinical outcomes and to reduce the costs of patient care. This paper presents a new graph processing framework for clinical data, which can leverage from cloud computing to address large-scale studies. Also, a case study of breast cancer with relevance for the clinical practice is presented. This case is successfully addressed using a dataset consisting of 15,000 reports from 1,000 anonymised patients, demonstrating the capability of the framework for indexing and searching large, heterogeneous datasets.