اکتشاف زمان واقعی و مدیریت مجموعه داده های حجمی پزشکی بزرگ بر دستگاه های کوچک همراه؛بررسی روش رندرینگ حجم از راه دور
|کد مقاله||سال انتشار||مقاله انگلیسی||ترجمه فارسی||تعداد کلمات|
|20195||2013||8 صفحه PDF||سفارش دهید||6225 کلمه|
Publisher : Elsevier - Science Direct (الزویر - ساینس دایرکت)
Journal : International Journal of Information Management, Available online 16 December 2013
In this paper I present the architecture of system that can be used for real time exploration and management of large medical volumetric datasets. The new state of the art solution presented in this paper is an example of visual data management system. System prototype evaluation proved that it is possible to use low-powered (and cheap) up-to-date mobile devices with programmable GPUs as the remote interfaces for exploration of large volumetric medical data. The implementation was done with high-level programming language that enables portability between different hardware models. The lack of lossy compression enables to display high quality medical images visualizations without any simplifications and noises in frequency domain. The prototype of system is capable to remotely render and send to a client (for example cell phone or tablet) rendered data with frequency 30 fps with limited resolution during interaction. One second after the interaction is finished client machine receives full resolution image. The evaluation of the system was performed on volumetric computed tomography angiography image with approximate size 5123 voxels.
Computer science is a strongly interdisciplinary branch of knowledge. In informatics, each new scientific and technical achievement that has potential to become valuable commercial product is very quickly deployed into multiple different disciplines of science. Because of this the rapid development in computer science often stimulates the progress of associated disciplines. This influence is especially visible in contemporary medicine and medical systems. Paper (Hachaj & Ogiela, 2013) presents selected applications of computer methods in the field of contemporary medical informatics. The remarkable impact of computer science and telecommunication on medicine is visible in the field of so-called Picture Archiving and Communication Systems (PACS). PACS system is a medical imaging technology that provides economical storage of and convenient access to images from multiple modalities (source machine types) (Mehmet, 2012). The concept of PACS was initiated in 1982, since then PACS have been matured to become an everyday clinical tool for image archiving, communication, display, and review (Huang, 2011). In some cases it is not necessary or not possible for doctor to have direct access to complicated PACS workstations or even face-to-face contact with particular patient (Hachaj & Ogiela, 2013). Report (Kho, Henderson, Dressler, & Kripalani, 2006) suggests that over the past decade, handheld computers (or personal digital assistants – PDAs) have become popular tools among medical trainees and physicians. Many medical students and residents use PDAs for educational purposes or patient care. Most of the studies included described PDA use for patient tracking and documentation, medical textbooks, medication references, and medical calculators as the most useful applications. A PDA can also supply physician with an interface for PACS system however in this case some very serious methodological and technological obstacles have to be overcome. One of the most remarkable problems is real-time visualization of patients’ volumetric datasets. Those datasets are mostly products of computed tomography (CT), magnetic resonance (MR), single-photon emission computed tomography (SPECT) or positron emission tomography (PET). Medical 3D visualization is considered real-time if it gives physician capability to interact with visualization by changing the position of observation, declaring clipping planes and modifying transparencies and colors of tissues without noticeable latency. In order to achieve this functionalities scientists and engineers has to incorporate they knowledge about remote rendering, data transmission and mobile devices programming. This paper proposes system architecture, implementation of prototype and its evaluation that uses small mobile devices (cell phone, tablets, etc.) for real time exploration of large medical datasets. The new state of the art solution presented in this paper is an example of visual data management system. This particular type of dataset was chosen because it seems to be one of the most challenging modalities to visualize (because of size and complexity) and also it is commonly used in imaging based diagnosis processes (Ogiela, 2008). In the next sections of this section the state of the art of remote rendering, data transmission and mobile devices programming will be presented. Then I will summarize papers about existing systems with similar capabilities as my proposition. I will also show advantage of my new solution over existing ones.
نتیجه گیری انگلیسی
The results of presented experiments proved that it is possible to use low-powered (and cheap) mobile devices as the remote interfaces for large volumetric medical data. The presented application manages real-time medical data exchanging and transmission procedure between centralized server and mobile devices. The implementation was done with high-level programming language that enables portability between different hardware models. The lack of lossy compression enables to display high quality medical images visualizations without any simplifications and noises in frequency domain. From the other hand lack of lossless compressions of 2D data increases the speed of image processing both in server and remote devices trading it for the cost of network latency. The prototype of system is capable to remotely render and send to client data with frequency 30 fps with limited resolution during interaction. One second after the interaction is finished client machine receive full resolution image. The new state of the art solution presented in this paper might be a good starting point for further improvements. At first it should be evaluated that how much different lossless compression algorithms affects the overall system performance. It also would be valuable to examine new secret splitting techniques based on mathematical linguistic methods (Ogiela & Ogiela, 2012). The second important goal for the future is employ 3G telecommunication networks for remote interaction and image data transfer. This will require adaptation of the proposed data transfer protocol to this particular technology.