Open Source Python Medical Software
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Python Medical Software
View 202 business solutionsBrowse free open source Python Medical Software and projects below. Use the toggles on the left to filter open source Python Medical Software by OS, license, language, programming language, and project status.
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Brain Workshop
Python implementation of the Dual N-Back mental exercise
Brain Workshop is a Python implementation of the Dual N-Back mental exercise. This exercise is the only mental activity that has been scientifically shown to improve your short-term memory (working memory) and fluid intelligence. -
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BioImageXD - free open source software for analysis, processing and 3D rendering of multi dimensional, multi data channel, time series image data from microscopy and other sources.
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Grassroots DICOM
Cross-platform DICOM implementation
Grassroots DiCoM is a C++ library for DICOM medical files. It is accessible from Python, C#, Java and PHP. It supports RAW, JPEG, JPEG 2000, JPEG-LS, RLE and deflated transfer syntax. It comes with a super fast scanner implementation to quickly scan hundreds of DICOM files. It supports SCU network operations (C-ECHO, C-FIND, C-STORE, C-MOVE). PS 3.3 & 3.6 are distributed as XML files. It also provides PS 3.15 certificates and password based mecanism to anonymize and de-identify DICOM datasets. -
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BioSig is a software library for processing of biomedical signals (EEG, ECG, etc.) with Matlab, Octave, C/C++ and Python. About 50 different data formats are supported.
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MAGeCK
Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout
MAGeCK2 is here: https://github.com/davidliwei/mageck2 Model-based Analysis of Genome-wide CRISPR-Cas9 Knockout (MAGeCK) is a computational tool to identify important genes from the recent genome-scale CRISPR-Cas9 knockout screens technology. For instructions and documentations, please refer to the wiki page. MAGeCK is developed by Wei Li and Han Xu from Dr. Xiaole Shirley Liu's lab at Dana-Farber Cancer Institute/Harvard School of Public Health, and is maintained by Wei Li lab at Children's National Medical Center. We thank the support from Claudia Adams Barr Program in Innovative Basic Cancer Research and NIH/NHGRI to develop MAGeCK. -
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niftilib
** MAIN SITE IS NOW: https://github.com/NIFTI-Imaging/nifti_clib **
niftilib is a collection of i/o routines for the nifti1 neuroimage data format. C (nifticlib), Java (niftijlib), Matlab (niftimatlib), and Python (pynifti) code is available. For nifti format info see: http://nifti.nimh.nih.gov/ -
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GNU Health
GNU Health - The Free/Libre Hospital and Health Information System
GNU Health is the award-winning Hospital and Health Information System (HIS), declared a Digital Public Good and adopted by the United Nations . GNU Health Hospital and Lab information system is used by academic and research institutions around the globe. It is also used in public health system of countries such as Argentina, India, Jamaica, Laos, Cameroon, Suriname. GNU Health is an official GNU project. GNU Health is brought to you by GNU Solidario, an Non-Profit Organization (NGO) that focuses in Social Medicine. -
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Febrl (Freely Extensible Biomedical Record Linkage) does data standardisation (segmentation and cleaning) and probabilistic record linkage ("fuzzy" matching) of one or more files or data sources which do not share a unique record key or identifier.
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OpenCMISS-Zinc
A Library for Interactive Modelling and Visualisation
The OpenCMISS-Zinc Library (opencmiss.org/zinc), or Zinc, is a software library for building interactive graphical modelling and visualisation applications. Models are represented in Zinc as mathematical fields defined over domains, including finite elements with support for high-order basis functions, complex parameter mappings and time variation, and image-based fields. Further fields can be defined by mathematical expressions and algorithms on existing fields, including image processing filters. Zinc model data structures are dynamic, supporting interactive applications which programmatically create, destroy and modify parts of models. -
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medical image analysis
Libraries and command line tools for medical image processing.
This software provides libraries and command line tools for the processing and analysis of gray scale medical images. -
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Gadgetron
Medical Image Reconstruction Framework
Medical Image Reconstruction Framework -
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This is a sophisticated & integrated simulation and analysis environment for dynamical systems models of physical systems (ODEs, DAEs, maps, and hybrid systems). It supports symbolic math, optimization, continuation, data analysis, biological apps...
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""" E-Cell's source code repository has moved to GitHub! https://github.com/ecell The development of E-Cell now continues on GitHub. The Subversion repository was abandoned. """ E-Cell System is an object-oriented software suite for modeling, simulation, and analysis of large scale complex systems such as biological cells. It allows many components driven by multiple algorithms with different timescales to coexist in a model.
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This project, developed at UCL London, provides code for tomographic reconstruction. NiftyRec is written in C and has Python and Matlab extensions. Computationally intensive functions have a GPU accelerated version based on CUDA.
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The new version of MinimPy (MinimPy2) is available for download at: https://osdn.net/dl/minimpy2/MinimPy2.zip Please send your feedback about this new version to mahmood.saghaei@gmail.com (include MinimPy2 in the subject) ============================================================ MinimPy is a desktop application program for sequential allocation of subjects to treatment groups in clinical trials by using the method of minimization. Comprehensive reference help is available at http://minimpy.sourceforge.net MinimPy has been fully described in the following article: Saghaei, M. and Saghaei, S. (2011) Implementation of an open-source customizable minimization program for allocation of patients to parallel groups in clinical trials. Journal of Biomedical Science and Engineering, 4, 734-739. doi: 10.4236/jbise.2011.411090. Available at: http://www.scirp.org/journal/PaperInformation.aspx?PaperID=8518
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SimPET
A web platform for the MC simulation of realistic brain PET data
SimPET (http://www.sim-pet.org) is an open, efficient, and user‐friendly online platform for the generation of synthetic brain PET datasets. The platform offers the ability to generate realistic activity and attenuation maps from patient's PET/CT and MRI images. These maps can then be simulated, and sinograms and simulated images can be downloaded. More advanced features can be obtained by using the SimPET scripts: https://github.com/txusser/brainviset_simset https://github.com/txusser/simpet (New version pre-alpha) You can also upload your own phantoms to simulate. Currently the platform incorporates MC models for the GE Advance, GE Discovery ST and Siemens mCT. More models are on the way. You can also access all the previously simulated datasets from the dev team to test your quantification pipeline (Files section in this page). This project is an open collaboration between IDIS (www.idisantiago.es), Qubiotech (www.qubiotech.es), and FGUMA (www.fguma.es). -
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pyQPCR is a GUI application written in python that deals with quantitative PCR (QPCR) raw data. Using quantification cycle values extracted from QPCR instruments, it uses a proven and universally applicable model to give finalized quantification resu
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The MITK Workbench is a free, open-source application for medical image visualization, segmentation, registration, and much more. Beyond the Workbench application, MITK is a comprehensive C++ framework for medical image computing. It provides a modular foundation for extending the MITK Workbench with custom plugins or developing your own medical imaging applications and research prototypes.
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XMIPP is an image processing suite for 3D-reconstruction of biological specimens from transmission electron microscopy data. NOTE that stable releases (including binaries) are longer stored at Sourceforge, but are available at http://xmipp.cnb.csic.es
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OmicSelector
Feature selection and deep learning modeling for omic biomarker study
OmicSelector is an environment, Docker-based web application, and R package for biomarker signature selection (feature selection) from high-throughput experiments and others. It was initially developed for miRNA-seq (small RNA, smRNA-seq; hence the name was miRNAselector), RNA-seq and qPCR, but can be applied for every problem where numeric features should be selected to counteract overfitting of the models. Using our tool, you can choose features, like miRNAs, with the most significant diagnostic potential (based on the results of miRNA-seq, for validation in qPCR experiments). -
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PocketAnalyzerPCA combines a geometric algorithm for detecting pockets in proteins with Principal Component Analysis and clustering. This enables visualization and analysis of pocket conformational distributions of large sets of protein structures.
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Py3DN
Morphometric analysis and visualization of the 3D structure of neurons
Py3DN, is an open-source solution providing innovative tools to analyze 3D data collected with the widely used commercial system Neurolucida (MBF). It allows the construction of mathematical representations of neuronal topology, visualization and a variety of morphometric analysis on the neuronal structures. Above all, it provides a flexible environment where new types of analyses can be easily set up allowing total freedom to test new hypotheses. The application was developed in Python and uses Blender (an open source program) to produce detailed 3D representations of raw and processed data. Py3DN is described in the paper: Aguiar P et al, "Versatile morphometric analysis and visualization of the three-dimensional structure of neurons", Neuroinformatics, 2013, 11(4):393-403 doi: 10.1007/s12021-013-9188-z -
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BATS
Bayesian Adaptive Trial Simulator
A user-friendly, quick simulator for Bayesian Multi-Arm Multi-Stage Trials -
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FociCounter is a simple and user-friendly program for analysis of gamma-H2AX foci. It allows to determine the number of foci in a single cell, a foci intensity as well as a cell intensity.
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MRI neonatal atlas app
Use this application to segment neonates mri brain scans
Thi application helps the segmentation of mri brain images into 6 tissue classes by using the T2 neonatal atlas available at http://www.brain-development.org.
