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Niftilib

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Niftilib is a set of i/o libraries for reading and writing files in the nifti-1 data format. nifti-1 is a binary file format for storing medical image data, e.g. magnetic resonance image (MRI) and functional MRI (fMRI) brain images.

Niftilib currently has C, Java, MATLAB, and Python libraries; we plan to add some MATLAB/mex interfaces to the C library in the not too distant future.

XMedCon

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The project stands for Medical Image Conversion. Released under the (L)GPL licence, it comes with the full C-source code of the library, a flexible command-line utility and a neat graphical front-end using the Gtk+ toolkit. The supported formats are: Acr/Nema 2.0, Analyze (SPM), Concorde/µPET, DICOM 3.0, CTI ECAT 6/7, NIfTI-1, InterFile3.3 and PNG or Gif87a/89a.

The 'epibasix' R Package

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This package contains elementary tools for analysis of common epidemiological problems, ranging from sample size estimation, through 2x2 contingency table analysis and basic measures of agreement (kappa, sensitivity/specificity).

Appropriate print and summary statements are also written to facilitate interpretation wherever possible.

This package is a work in progress, so any comments or suggestions would be appreciated. Source code is commented throughout to facilitate modification. The target audience includes graduate students in various epi/biostatistics courses.

Brainstorm

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Brainstorm is a collaborative open-source Matlab application dedicated to magnetoencephalography (MEG) and electroencephalography(EEG) data visualization, processing and cortical source estimation.
The intention is to make a comprehensive set of tools available to the scientific community involved in MEG/EEG experimental research.
For physicians and researchers, the interest of this software package resides in its rich and intuitive graphic interface, which does not require any programming knowledge.

The 'epicalc' R Package

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Functions making R easy for epidemiological calculation.

Datasets from Dbase (.dbf), Stata (.dta), SPSS(.sav), EpiInfo(.rec) and Comma separated value (.csv) formats as well as R data frames can be processed to do make several epidemiological calculations.

CASE

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The main goal of the Computer Assisted Search for Epidemics (CASE) project is to develop a reliable system that generates warnings when the number of reported cases of a particular infectious disease reaches a level that indicates an unusual or unexpected rate. The system is currently in use at the Swedish Institute for Infectious Disease Control (SMI). It performs daily surveillance using data obtained from the database to which all notifiable diseases are reported in Sweden.

FreeSHIM

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FreeSHIM is an opensource electronic medical device interface, which aims to allow any EMR/PM system to talk to any medical device attached to a workstation without having to install tons of pesky drivers or “reinvent the wheel” for each additional device manufacturer.

It is written in Java, and has been tested on Linux and Windows workstations (though we’re pretty sure it also runs fine on Mac OS X as well), and exposes both SOAP and REST interfaces. Its only prerequisite is a running J2EE container, such as Apache Tomcat.

Java Light PACS Viewer (jlpv)

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jlpv is a Java Light PACS Viewer application useful for review series or images from DICOM data retrieved from the DCM4CHEE PACS system. It also uses ImageJ as a rendering engine or viewer. This project is in a early stage.

REMITT

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REMITT is a revolutionary medical information translation and transmission system, which is primarily used for preparing and submitting medical billing data.

REMITT works independent of any specific electronic medical record (EMR) or practice management (PM) system, and can interface with any EMR or PM system which implements its application programming interface (API). The first system to do so has been FreeMED.

Currently Supported Formats

  • HCFA-1500/CRM-1500
  • ANSI NSF X12 837 Professional

Currently Supported Output Types

The 'epiR' R Package

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A package for analysing epidemiological data. Contains functions for directly and indirectly adjusting measures of disease frequency, quantifying measures of association on the basis of single or multiple strata of count data presented in a contingency table, and computing confidence intervals around incidence risk and incidence rate estimates. Miscellaneous functions for use in meta-analysis, diagnostic test interpretation, and sample size calculations.

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