Search Results for "java medical imaging"
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6 projects for "java medical imaging" with 2 filters applied:
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Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. -
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El proyecto central es la conformación de un Sistema de Información Hospitalaria, se pretende ir por subproyectos los cuales formaran las piezas fundamentales que se integraran mediante perfiles IHE que vayan estableciéndose para la norma HL7v3
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dicom related framework and applications in java. The project is divide in 3 parts, the framework, a dicom toolkit, and dicom apps.
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The Health Manager Java SDK is an interface definition to connect wireless medical devices with a Java application. It includes also an implementation that simulates real devices and a sample application demonstrating the usage.
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Enterprise-grade ITSM, for every businessFreshservice is an intuitive, AI-powered platform that helps IT, operations, and business teams deliver exceptional service without the usual complexity. Automate repetitive tasks, resolve issues faster, and provide seamless support across the organization. From managing incidents and assets to driving smarter decisions, Freshservice makes it easy to stay efficient and scale with confidence.
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MobHealth is an extensible mobile health framework/API written in JavaME. The current version supports two sensor-data formats (e.g. used by AliveTec). It already provides higher-level classes for data recognition like body position or hypoxia-detection.
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NESD-Imaging is a 2D rendering framework for Java. It combines JAI and Java2D and extends them by providing lazy rendering (do not block UI). It provides geo-positionned images rendering (à la google-map). It scales well to large image set (>500GB).
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