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CDMEDIC PACS WEB

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Your rating: None Average: 3.8 (15 votes)

Full featured free PACS based on ctn or dcm4chee, dcmtk and mysql, with remote accessiom using apache and perl available for Linux in Debian packaging format for i386, amd64 and Mac OS darwin i386 and ppc.

Perl HL7 Toolkit

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Your rating: None Average: 5 (1 vote)

This project provides a simple but flexible Perl Toolkit for using the HL7 protocol. The toolkit consists of a Perl API, an implementation of a pluggable forking HL7 server, and an HL7 message queue daemon for developing HL7 capable applications in Perl.

tinyHeb

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Your rating: None Average: 3.7 (3 votes)

tinyHeb is a billing software for midwives in Germany to do the legal accounting with the health insurance companies in Germany. tinyHeb runs under Linux and Windows operating systems. It enables the midwives to produce paper and electronic bills, and meets the legal requirements of §301a, §302 SGB V, resp. The tariff structure introduced in 2007 is no problem at all.

Mayam

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Your rating: None Average: 1.9 (9 votes)

A Cross-platform DICOM viewer developed in Java using the dcm4che toolkit. Mayam is still work under progress. The current features are:

  • DICOM Listener for Q/R
  • DICOM Send
  • Local DB for storing study information
  • Importing DICOM studies from local disk
  • Parsing DicomDir from local disk or CD
  • Query compressed studies without decompressing them
  • Multiple Studies viewer using Layout,Tab view

iRad

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Your rating: None Average: 3 (1 vote)

Rad is a DICOM workstation written in Cocoa for MacOSX. Using QuickTime, OpenGL, and open source databases iRad aims to provide an easy and efficient way to review medical images from CT, MRI, ultrasound, and other DICOM sources such as angiography.

GT.M

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GT.M is a FOSS (AGPL v3) implementation of M (also known as MUMPS), a combination of a procedural programming language well integrated with a hierarchical key-value database engine. M is widely used in enterprise scale healthcare applications and application suites, such as the VistA implementations. GT.M scales up to very large databases (the largest production sites have aggregate databases to several TB) and thousands of concurrent users.

RANDI2

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Your rating: None Average: 2.7 (7 votes)

RANDI2 is an open source web application for randomization within clinical trials. It supports a variety of randomization algorithms and offers a very useful set of functions for randomization data & progress visualization and trial management - for more information please visit http://www.randi2.org

ImmunoRatio

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Your rating: None Average: 3.3 (12 votes)

ImmunoRatio is a free web application for automated image analysis of estrogen receptor (ER), progesterone receptor (PR), and Ki-67 immunostained tissue sections.

The application:

  1. segments diaminobenzidine-stained (DAB) and hematoxylin-stained nuclei regions from the user-submitted image,
  2. calculates the percentage of DAB-stained nuclear area over total nuclear area (=labeling index), and
  3. generates a pseudo-colored result image matching the area segmentation (see the example on right side).

EGADSS

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Your rating: None Average: 1.9 (10 votes)

EGADSS (Evidence-based Guideline and Decision Support System) is an open source tool that is designed to work in conjunction with primary care Electronic Medical Record (EMR) systems to provide patient specific point of care reminders in order to aid physicians provide high quality care. EGADSS is designed as a stand alone system that would respond to requests from existing Electronic Medical Records such as Wolf, Med Access, and MedOffIS to provide patient specific clinical guidance based on its internal collection of guidelines.

Snofyre

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Snofyre is an open source, service oriented API for creating SNOMED CT enabled applications in Java. It provides a number of SNOMED CT related services out of the box. These services can be used:

  • as a starter for understanding how to add SNOMED CT functionality to an application.
  • to rapidly prototype a SNOMED CT enabled application.

Snofyre API aims to

  • reduce the 'ramp up' time needed to understand
  • and embed SNOMED CT functionality in an application.

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