149 projects tagged "Medical Science"
GNotary is a set of Python scripts that implement an asynchronous digital notary service. Anybody who needs certification of any digital document creates a message digest (like MD5 or RIPEMD160) of that document and submits it to the GNotary service by email. GNotary signs this email digitally (using GnuPG), retains a copy of the certified and time stamped message, and mails it back to the sender, optionally with the public key attached to allow the sender to verify the signed document. At regular intervals, the GNotary server creates message digests of its own logs and distributes them among other GNotary servers, thus making it virtually impossible to forge the chain of evidence that authenticates a submitted document.
Renal Growth is a tool for radiologists and paediatricians to plot renal length and volume measurements against nomograms for age and weight. It allows for multiple observations from birth to 13 years. Individual patient data files can be stored and reused. Length and volume charts can be exported as JPEG files for importing into a PACS system or other clinical record.
SENTENSA Knowledge Miner is a platform independent tool for searching any text. SENTENSA uses robust methods of indexing and searching text, leveraging experience from more than 20 years of information retrieval. SENTENSA products offer advanced text retrieval solutions for large databases that will make your searches for key information fast and effective. You can index on one platform and query on another.
MeVisLab is a platform for image processing research and development with a focus on medical imaging. It allows fast integration and testing of new algorithms and the development of application prototypes that can be used in clinical environments. Beside general image processing algorithms and visualization tools, MeVisLab includes advanced medical imaging modules for segmentation, registration, volumetry, and quantitative morphological and functional analysis.
Kradview is a viewer of images obtained from different sources such as X-ray, NMR, and DICOM-compatible imaging devices. Its aim is to be an easy-to-use DICOM viewer with instant rendering of images, no matter the size and the zoom of the DICOM image. It allows medical professionals to view X-ray images easily.