You are here

Project Wizard

You can use the category filters given on the right sidebar to narrow down your search results.

PixelMed Java DICOM Toolkit

Rating: 
Your rating: None Average: 3.6 (15 votes)

PixelMed Java DICOM Toolkit is a stand-alone DICOM toolkit that implements code for reading and creating DICOM data, DICOM network and file support, a database of DICOM objects, support for display of directories, images, reports and spectra, and DICOM object validation.

The toolkit is a completely new implementation, which does not depend on any other DICOM tools, commercial or free. It does make use of other freely available pure Java tools for compression and XML and database support.

Nukak3D

Rating: 
Your rating: None Average: 1.4 (7 votes)

3D medical image platform for visualization and image processing. Segmentation with Levels sets. Surface reconstruction with marching Cubes, texture Mapping and Raycasting, DICOM support.

Grassroots DICOM (GDCM)

Rating: 
Your rating: None Average: 3.7 (11 votes)

Grassroots DICOM (GDCM) is an implementation of the DICOM standard designed to be open source so that researchers may access clinical data directly. GDCM includes a file format definition and a network communications protocol, both of which should be extended to provide a full set of tools for a researcher or small medical imaging vendor to interface with an existing medical database.

Niftilib

Rating: 
Your rating: None Average: 3 (3 votes)

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.

MRmap

Rating: 
Your rating: None Average: 3.2 (14 votes)

MRmap is a flexible software tool that enables T1, T2, and T2* mapping from source images of multiple types of pulse sequences (IR-prepared multi-image T1 mapping, Look-Locker/ TOMROP T1 mapping, MOLLI T1 mapping; single- and multi-echo T2/ T2* mapping).

MRmap is a pure research tool and is not intended for any diagnostic or clinical use.

Vurtigo

Rating: 
Your rating: None Average: 3 (3 votes)

Vurtigo is a four-dimensional (3D + time) real-time visualization software for guiding cardiovascular interventions. It is designed to be part of a pipeline that can connect it to a magnetic resonance imaging (MRI) scanner, actively tracked catheters, and navigational devices.

Written in C++ under the GNU Lesser General Public License v2.1, Vurtigo features a plug-in based architecture, allowing developers to extend the software using an interface to manipulate objects within Vurtigo. The software runs on Win32, Linux and Mac OS X.

OpenSourcePACS

Rating: 
Your rating: None Average: 3.9 (22 votes)

OpenSourcePACS is a free, open source image referral, archiving, routing and viewing system. It adds functionality beyond conventional PACS by integrating wet read functions, implemented through DICOM Presentation State and Structured Reporting standards.

In its first release, OpenSourcePACS delivers a complete wet read system, enabling an imaging clinic or hospital to offer its services over the web to physicians within or outside the institution. In future releases, we hope to incorporate more RIS (dictation, transcription, and reporting) functionality.

JULIDE

Rating: 
No votes yet

JULIDE is a software toolkit developed to perform the 3D reconstruction, intensity normalization, volume standardization by 3D image registration and voxel-wise statistical analysis of autoradiographs of mouse brain sections.

RT_Image

Rating: 
Your rating: None Average: 4 (4 votes)

RT_Image is an application developed in the Department of Radiation Oncology and MIPS at Stanford University. Coded in the Interactive Data Language (IDL, ITT Visual Information Solutions), RT_Image was originally designed in 2003 to generate radiotherapy target volumes from positron emission tomography (PET) datasets. It has since evolved to embody a variety of tools for visualizing, quantitating, and segmenting three-dimensional images.

Pages