Nowadays, biomedicine is characterised by a growing need for processing of large amounts of data in real time. This leads to new requirements for information and communication technologies (ICT). Cloud computing offers a solution to these requirements and provides many advantages, such as cost savings, elasticity and scalability of using ICT. The aim of this paper is to explore the concept of cloud computing and the related use of this concept in the area of biomedicine. Authors offer a comprehensive analysis of the implementation of the cloud computing approach in biomedical research, decomposed into infrastructure, platform and service layer, and a recommendation for processing large amounts of data in biomedicine. Firstly, the paper describes the appropriate forms and technological solutions of cloud computing. Secondly, the high-end computing paradigm of cloud computing aspects is analysed. Finally, the potential and current use of applications in scientific research of this technology in biomedicine is discussed.
... Lowson -- The ‘CommuniCare’ patient-based community computer 74 system -- GC Curwen and DW Harrison - ... ... in the general dental services: 118 a view from the DPB -- RMP Nicholson -- Computer support for clinical ... ... Dale, and KL Stein -- Consultants’ views on their use of a computer-based 217 medical record system D ... ... -- Enhancing medical information access with a palmtop 759 computer -- JG Ard -- Computer facial imaging ... ... Owen-Smith -- Computer technology of synthetic diagnostics of 792 psychogenic diseases -- Z Brelidze, ...
First published xxiv, 836 stran : ilustrace, tabulky ; 21 cm
- MeSH
- Medical Informatics MeSH
- Publication type
- Congress MeSH
- Collected Work MeSH
- Conspectus
- Lékařské vědy. Lékařství
- NML Fields
- lékařská informatika
Infrastruktura jako služba, tedy infrastruktura poskytovaná zákazníkovi formou služby poskytovatele, je jedním z modelu nasazení tzv. cloud computingu, který umožňuje využít datovou a výpočetní kapacitu v cloudu jako množinu fyzických či virtuálních zařízení. Infrastruktura jako služba může být poskytována zvlášť každému výzkumnému projektu a přitom sdílet stejné fyzické kapacity zapojených počítačů a zařízení. V současné době je testováno poskytování infrastruktury jako služby několika projektům v rámci aktivit sdružení CESNET, 1. lékařské fakulty Univerzity Karlovy v Praze (1. LF UK) a Hudební a taneční fakulty Akademie múzických umění v Praze (HAMU). Současný výzkum v oblasti výpočetní fyziologie je náročný na výpočetní kapacitu. Výpočetní úlohy jsou distribuovány počítačům, které jsou poskytovány infrastrukturou. Projekt v oblasti analýzy lidského hlasu je náročný na propustnost počítačové sítě mezi akustickým a video zařízením na lokální straně a analytickou aplikací na straně výkonného serveru. Tento příspěvek popisuje hlavní vlastnosti a výzvy pro infrastruktury určené pro takovýto typ aplikací. Infrastruktura jako model nasazení v rámci cloud computingu může být vhodná pro mezioborové týmy a pro spolupráci a integraci vysoce specializovaných softwarových aplikací.
Infrastructure as a service (infrastructure which is offered to a customer in the form of service of the provider) is a deployment model which allows utilize data and computing capacity of a cloud as a set of virtual devices and virtualized machines. Infrastructure as a service can be offered separately to each project. The same capacity of connected physical machines and devices can be shared. Currently, the concept of an Infrastructure as a service is tested on several projects within activity of the CESNET association, First Faculty of Medicine, Charles University, Prague and Musical and Dance Faculty of Academy of Performing Arts in Prague. The current research in the field of computation physiology is demanding on a high computation capacity. The computation tasks are distributed to computers, which are provided by the infrastructure. The project in the field of the analysis of a human voice is demanding on high throughput of a computer network between an acoustic or video device on the local side and an analytic application on the remote high performance server side. This paper describes features and main challenges for infrastructure dedicated for such a type of an application. Infrastructure as a deployment model of cloud computing might be beneficial for a multi domain team and for collaboration and integration of a high specialized software application.
- Keywords
- infrastruktura jako služba, virtualizace, virtualizace, výpočetní fyziologie, identifikace fyziologických systémů, validace fyziologických systémů, protokol vzdálené plochy, grid computing, hlasové pole,
- MeSH
- Biomedical Technology MeSH
- Cloud Computing MeSH
- Financing, Organized MeSH
- Computer Communication Networks organization & administration trends utilization MeSH
- Computer Systems trends utilization MeSH
- Medical Informatics Applications MeSH
Many hospitals and medical clinics have been using a wearable sensor in its health care system because the wearable sensor, which is able to measure the patients' biometric information, has been developed to analyze their patients remotely. The measured information is saved to a server in a medical center, and the server keeps the medical information, which also involves personal information, on a cloud system. The server and network devices are used by connecting each other, and sensitive medical records are dealt with remotely. However, these days, the attackers, who try to attack the server or the network systems, are increasing. In addition, the server and the network system have a weak protection and security policy against the attackers. In this paper, it is suggested that security compliance of medical contents should be followed to improve the level of security. As a result, the medical contents are kept safely.
- MeSH
- Algorithms MeSH
- Monitoring, Ambulatory instrumentation MeSH
- Biometry MeSH
- Medical Records MeSH
- Cloud Computing * MeSH
- Confidentiality MeSH
- Electronic Health Records MeSH
- Internet MeSH
- Medical Informatics instrumentation MeSH
- Humans MeSH
- Delivery of Health Care MeSH
- Programming Languages MeSH
- Data Collection MeSH
- Information Storage and Retrieval methods MeSH
- Computer Security * MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- MeSH
- Cloud Computing trends MeSH
- Hospital Information Systems MeSH
- Computer Security MeSH
- Publication type
- Newspaper Article MeSH
593 s.
The purpose of this study is (1) to introduce a new approach for edge detection in orthopantograms (OPGs) and an improved automatic parameter selector for common edge detectors, (2) to present a comparison between our novel approach with common edge detectors and (3) to provide faster outputs without compromising quality. A new approach for edge detection based on statistical measures was introduced: (1) a set of N edge detection results is calculated from a given input image and a selected type of edge detector, (2) N correspondence maps are constructed from N edge detection results, (3) probabilities and average probabilities are computed, (4) an overall correspondence is evaluated for each correspondence map and (5) the correspondence map providing the best overall correspondence is taken as the result of edge detection procedure. A comparison with common edge detectors (the Roberts, Prewitt, Sobel, Laplacian of the Gaussian and Canny methods) with various parameter settings (304 combinations for each test image) was carried out. The methods were assessed objectively [edge mismatch error (EME), modified Hausdorff distance (MHD) and principal component analysis] and subjectively by experts in dentistry and based on time demands. The suitability of the new approach for edge detection in OPGs was confirmed by experts. The current conventional methods in edge detection in OPGs are inadequate (none of the tested methods reach an EME value or MHD value below 0.1). Our proposed approach for edge detection shows promising potential for its implementation in clinical dentistry. It enhances the accuracy of OPG interpretation and advances diagnosis and treatment planning.
- MeSH
- Algorithms MeSH
- Principal Component Analysis MeSH
- Anatomic Landmarks radiography MeSH
- Artifacts MeSH
- Time Factors MeSH
- Jaw Cysts radiography MeSH
- Tooth Extraction MeSH
- Humans MeSH
- Normal Distribution MeSH
- Image Processing, Computer-Assisted statistics & numerical data MeSH
- Probability MeSH
- Radiography, Panoramic statistics & numerical data MeSH
- Radiographic Image Interpretation, Computer-Assisted methods MeSH
- Dental Caries radiography MeSH
- Tooth, Supernumerary radiography MeSH
- Check Tag
- Humans MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Comparative Study MeSH
