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.
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The MedicalExplorationToolkit (METK) was designed for loading, visualizing and exploring segmented medical data sets. It is a framework of several modules in MeVisLab, a development environment for medical image processing and visualization.
- Case Management: Load and save whole cases of segmented structures e.g. for surgery planning, educational training or intra operative visualization.
- Basic Visualization in 2D and 3D: Visualize segmented structures in multiple manner e.g. iso surface rendering, stippling, hatching, silhouettes, volume rendering, 2d overlays.
DICOM basic constructs used to create the tools at CharruaSoft.com. Its C++ code is a re-interpretation of the original UCDMC library by Mark Oskin. It tries to be much simpler and compact, also uses many Borland VCL specific structures.
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.
The purpose of the dicom4j platform is to provide java components related to the Dicom Standard. For those purpose, the platform is based on 4 areas:
- framework: framework which implements the standards
- toolkit: offer ways to easily develop software based on the framework
- plugins: end-user components which adress commons needs you can find in most dicom applications
- apps: stand alone applications for end-user or tests purpose
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.
The HL7 Inspector is a useful hl7 tool for integration the HL7 in a health care environmental. It will help you to minimize the time for tuning the HL7 communication between systems such as HIS and RIS by analyzing and validating HL7 messages.
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.
HAPI (HL7 application programming interface; pronounced "happy") is an open-source, object-oriented HL7 2.x parser and encoder for HL7 version 2.x messages written in Java. This project is not affiliated with the HL7 organization; we are just writing some software that conforms to their specification. The project was initiated by University Health Network (a large multi-site teaching hospital in Toronto, Canada).
Occupancy in certain hospital patient care units is impacted by procedure scheduling policies and practices. For example, intensive care unit occupancy is strongly related to open heart surgery schedules. Similarly, occupancy in obstetrical postpartum units is impacted by the daily number of scheduled labor inductions and cesarean sections. That was the motivation for this project.
OBsched is a set of optimization models and supporting software for exploring the relationship between patient scheduling and nursing unit occupancy in hospitals.