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RT_Image

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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.

Nukak3D

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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.

MRmap

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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.

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.

ParaView

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Your rating: None Average: 4 (1 vote)

ParaView is an open-source, multi-platform data analysis and visualization application. ParaView users can quickly build visualizations to analyze their data using qualitative and quantitative techniques. The data exploration can be done interactively in 3D or programmatically using ParaView's batch processing capabilities.

ParaView was developed to analyze extremely large datasets using distributed memory computing resources. It can be run on supercomputers to analyze datasets of terascale as well as on laptops for smaller data.