Many studies have indicated that computing technology can enable off-site cardiologists to read patients’ electrocardiograph (ECG), echocardiography (ECHO), and relevant images via smart phones during pre-hospital, in-hospital, and post-hospital teleconsultation, which not only identifies emergency cases in need of immediate treatment, but also prevents the unnecessary re-hospitalizations. Meanwhile, several studies have combined cloud computing and mobile computing to facilitate better storage, delivery, retrieval, and management of medical files for telecardiology. In the future, the aggregated ECG and images from hospitals worldwide will become big data, which should be used to develop an e-consultation program helping on-site practitioners deliver appropriate treatment. With information technology, real-time tele-consultation and tele-diagnosis of ECG and images can be practiced via an e-platform for clinical, research, and educational purposes. While being devoted to promote the application of information technology onto telecardiology, we need to resolve several issues: (1) data confidentiality in the cloud, (2) data interoperability among hospitals, and (3) network latency and accessibility. If these challenges are overcome, tele-consultation will be ubiquitous, easy to perform, inexpensive, and beneficial. Most importantly, these services will increase global collaboration and advance clinical practice, education, and scientific research in cardiology.

https://www.mdpi.com/1660-4601/10/11/6131/pdf

Mobile, Cloud, and Big Data Computing: Contributions, Challenges, and New Directions in Telecardiology

To develop a generic Open Source MRI perfusion analysis tool for quantitative parameter mapping to be used in a clinical workflow and methods for quality management of perfusion data. We implemented a classic, pixel-by-pixel deconvolution approach to quantify T1-weighted contrast-enhanced dynamic MR imaging (DCE-MRI) perfusion data as an OsiriX plug-in. It features parallel computing capabilities and an automated reporting scheme for quality management. Furthermore, by our implementation design, it could be easily extendable to other perfusion algorithms. Obtained results are saved as DICOM objects and directly added to the patient study. The plug-in was evaluated on ten MR perfusion data sets of the prostate and a calibration data set by comparing obtained parametric maps (plasma flow, volume of distribution, and mean transit time) to a widely used reference implementation in IDL. For all data, parametric maps could be calculated and the plug-in worked correctly and stable. On average, a deviation of 0.032 ± 0.02 ml/100 ml/min for the plasma flow, 0.004 ± 0.0007 ml/100 ml for the volume of distribution, and 0.037 ± 0.03 s for the mean transit time between our implementation and a reference implementation was observed. By using computer hardware with eight CPU cores, calculation time could be reduced by a factor of 2.5. We developed successfully an Open Source OsiriX plug-in for T1-DCE-MRI perfusion analysis in a routine quality managed clinical environment. Using model-free deconvolution, it allows for perfusion analysis in various clinical applications. By our plug-in, information about measured physiological processes can be obtained and transferred into clinical practice.

UMMPerfusion: an open source software tool towards quantitative MRI perfusion analysis in clinical routine.

The conception and deployment of cost effective Picture Archiving and Communication Systems (PACS) is a concern for small to medium medical imaging facilities, research environments, and developing countries' healthcare institutions. Financial constraints and the specificity of these scenarios contribute to a low adoption rate of PACS in those environments. Furthermore, with the advent of ubiquitous computing and new initiatives to improve healthcare information technologies and data sharing, such as IHE and XDS-i, a PACS must adapt quickly to changes. This paper describes Dicoogle, a software framework that enables developers and researchers to quickly prototype and deploy new functionality taking advantage of the embedded Digital Imaging and Communications in Medicine (DICOM) services. This full-fledged implementation of a PACS archive is very amenable to extension due to its plugin-based architecture and out-of-the-box functionality, which enables the exploration of large DICOM datasets and associated metadata. These characteristics make the proposed solution very interesting for prototyping, experimentation, and bridging functionality with deployed applications. Besides being an advanced mechanism for data discovery and retrieval based on DICOM object indexing, it enables the detection of inconsistencies in an institution's data and processes. Several use cases have benefited from this approach such as radiation dosage monitoring, Content-Based Image Retrieval (CBIR), and the use of the framework as support for classes targeting software engineering for clinical contexts.

/pdf/anatomy-of-an-extensible-open-source-pacs-2u1f4pygei.pdf

Anatomy of an Extensible Open Source PACS

From the Divis (P.A.P., M.E.S Medicine, Dur Washington U Baltimore, M Germany (R. Maryland (D. Tennessee (B Hackensack U Healthcare, H Mountain View Oregon Healt Clinic, Clevel Chicago, Illino Ontario, Can Bioengineerin Menlo Park, DeBakey Hea (M.L.M., S.F University o Institute/Lava General Hosp M.S.-C.); the Philips Healt Irvine, Califor (G.S.S.); Yale Imaging, Nor San Francis Pennsylvania Center, Wash

American Society of Echocardiography Cardiovascular Technology and Research Summit: A Roadmap for 2020

We present a technological process based on the 3D Slicer software for the three-dimensional study of the brain's ventricular system with teaching purposes. It values the morphology of this complex brain structure, as a whole and in any spatial position, being able to compare it with pathological studies, where its anatomy visibly changes. 3D Slicer was also used to obtain volumetric measurements in order to provide a more comprehensive and detail representation of the ventricular system. We assess the potential this software has for processing high resolution images, taken from Magnetic Resonance and generate the three-dimensional reconstruction of ventricular system.

Morphological and Volumetric Assessment of Cerebral Ventricular System with 3D Slicer Software

Open Source software and social networks: disruptive alternatives for medical imaging.

OsiriX is an ‘open source’ multimodality medical imaging software that has gained huge popularity in areas of medicine where advance image processing and visualisation are needed. An increasing number of surgeons, particularly orthopaedic surgeons, are adopting this software platform for better assessment of musculoskeletal images from different imaging modalities such as magnetic resonance imaging (MRI), computed tomography (CT), or even hybrid positron emission tomography (PET)-CT. The ability to easily generate 3D and 4D images in realtime, with a convenient and user-friendly interface for interactive navigation, through large sets of image data allows for better diagnostic interpretation and treatment planning.

Joris Heuberger

Papers

Open Source software and social networks: disruptive alternatives for medical imaging.

Clinical Applications of OsiriX for Orthopaedic and Musculoskeletal Imaging