General purpose medical digital library definition

The need of an approach for the definition of a platform-independent medical digital library, using only 2 open-source tools, will be described. To test the need and the success of such an approach, a library will 3 be created, which can later be used in a larger scale as a general purpose digital medical tool, when comes 4 the need to evaluate an image. 5 As a first test, the library will be used in the development of a tool aimed to aid doctors in otoplasty 6 candidates' evaluation. This tool shall be developed and tested first on a mobile platform, so the potential 7 of the developed library can be tested on the most adverse situation. Also, the resulting library will be 8 license free, making easier the collaboration of others in development and integration with other software, 9 translating in a better spread of the library in medical practice. 10 CCS Concepts 11 • Medical imaging, mobile devices, digital medical tool. 12 Keywords 13 Medical imaging, open-source, image analysis software library, digital medical tool

CAMMD: Context Aware Mobile Medical Devices

Telemedicine applications on a medical practitioners mobile device should be context-aware. This can vastly improve the effectiveness of mobile applications and is a step towards realising the vision of a ubiquitous telemedicine environment. The nomadic nature of a medical practitioner emphasises location, activity and time as key context-aware elements. An intelligent middleware is needed to effectively interpret and exploit these contextual elements. This paper proposes an agent-based architectural solution called Context-Aware Mobile Medical Devices (CAMMD). This framework can proactively communicate patient records to a portable device based upon the active context of its medical practitioner. An expert system is utilised to cross-reference the context-aware data of location and time against a practitioners work schedule. This proactive distribution of medical data enhances the usability and portability of mobile medical devices. The proposed methodology alleviates constraints on memory storage and enhances user interaction with the handheld device. The framework also improves utilisation of network bandwidth resources. An experimental prototype is presented highlighting the potential of this approach

Emergency TeleOrthoPaedics m-health system for wireless communication links

For the first time, a complete wireless and mobile emergency TeleOrthoPaedics system with field trials and expert opinion is presented. The system enables doctors in a remote area to obtain a second opinion from doctors in the hospital using secured wireless telecommunication networks. Doctors can exchange securely medical images and video as well as other important data, and thus perform remote consultations, fast and accurately using a user friendly interface, via a reliable and secure telemedicine system of low cost. The quality of the transmitted compressed (JPEG2000) images was measured using different metrics and doctors opinions. The results have shown that all metrics were within acceptable limits. The performance of the system was evaluated successfully under different wireless communication links based on real data

Sensor, Signal, and Imaging Informatics in 2017.

Objective To summarize significant contributions to sensor, signal, and imaging informatics literature published in 2017.Methods PubMed® and Web of Science® were searched to identify the scientific publications published in 2017 that addressed sensors, signals, and imaging in medical informatics. Fifteen papers were selected by consensus as candidate best papers. Each candidate article was reviewed by section editors and at least two other external reviewers. The final selection of the four best papers was conducted by the editorial board of the International Medical Informatics Association (IMIA) Yearbook.Results The selected papers of 2017 demonstrate the important scientific advances in management and analysis of sensor, signal, and imaging information.ConclusionThe growth of signal and imaging data and the increasing power of machine learning techniques have engendered new opportunities for research in medical informatics. This synopsis highlights cutting-edge contributions to the science of Sensor, Signal, and Imaging Informatics

Mobile Image Ratiometry: A New Method for Instantaneous Analysis of Rapid Test Strips

Here we describe Mobile Image Ratiometry (MIR), a new method for the automated quantification of standardized rapid immunoassay strips using consumer-based mobile smartphone and tablet cameras. To demonstrate MIR we developed a standardized method using rapid immunotest strips directed against cocaine (COC) and its major metabolite, benzoylecgonine (BE). We performed image analysis of three brands of commercially available dye-conjugated anti-COC/BE antibody test strips in response to three different series of cocaine concentrations ranging from 0.1 to 300 ng/ml and BE concentrations ranging from 0.003 to 0.1 ng/ml. These data were then used to create standard curves to allow quantification of COC/BE in biological samples. MIR quantification of COC and BE proved to be a sensitive, economical, and faster alternative to more costly methods, such as gas chromatography-mass spectrometry, tandem mass spectrometry, or high pressure liquid chromatography. MIR is a valuable tool that provides instant data acquisition, tracking and analysis for the emerging field of mobile platform informatics (MPI)

Effects of smartphone sensor characteristics on dermatoscopic images : a simulation study

Dermatoscopes are commonly used to evaluate skin lesions. The rising incidence of skin cancer has led to a wide array of medical imaging devices entering the market, some of which provide the patient the ability to analyze skin lesions themselves. They usually come in the form of smartphone attachments or mobile applications that leverage the optics of the smartphone to acquire the image; and in some cases, even give a preliminary diagnosis. In this digital age these devices look to ease the burden of having to visit a dermatologist multiple times. While these attachments are no doubt very useful, the image sensors used within smartphones are limited in terms of how much information they can process and effectively output to the user. Smartphone sensors are also very small which can result in a less detailed image as opposed to one from a professional camera. Our work is focused on the analysis of the information lost due to the known limitations of smartphone sensors, and its effect on the image appearance. This analysis has been performed using a virtual simulation pipeline for dermatology called VCT-Derma, which contains a module for a proprietary dermatoscope whose optical stack parameters will be adapted to the smartphone sensor specifications mentioned in this manuscript. This manuscript also describes the necessary sensor parameters required for adapting the simulation model, the software used along with any assumptions made, perceived differences in the resulting images, as well as the direction of the ongoing work