The Wolfram Solution forMedical ImagingUse built-in functions for segmentation, registration, restoration, and image analysis; prototype new algorithms quickly and efficiently; and deploy tools as standalone or web-based applications—all from one system. The Wolfram medical imaging solution provides a complete integrated workflow for image processing and application development with the speed and performance benefits of GPU and parallel computation. |
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Mathematica includes thousands of built-in functions and curated data on many topics that let you:
- Design software programs to do edge-preserving smoothing, denoising, sharpening, and other enhancements
- Create pattern-recognition algorithms for computer-aided diagnosis or tumor detection
- Develop and simulate radio-frequency pulse sequences
- Scan cell samples for abnormalities
- Study videos of runners to improve the efficiency of their movements
- Deblur CT slices and remove inhomogeneities from MRI backgrounds
- Capture and process images from imaging devices in real time
- Analyze fiber orientation in lab-grown tissue to determine its strength
- Use noninvasive techniques to study the heart, reducing risk to the patient
- Deploy web applications for remote diagnosis
Using blob-analysis techniques find cells in a microscopic image
Creating interactive tools for analyzing images
Does your current tool set have these advantages?
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Complete, integrated image processing workflow in a single document
Matlab requires purchasing extra toolboxes for image processing and opening multiple windows to work with multiple images -
Extensive built-in image processing functions on any platform
ImageJ requires downloading and installing plug-ins created by varied sources for full functionality; OsiriX is only available for Mac operating systems -
Procedural, functional, and rule-based programming paradigms, plus easily recognizable function names, create an efficient programming environment
Matlab and other programs use primarily procedural languages, creating longer code, and use abbreviated function names that provide no intuitive indication of their meaning -
Conveniently drag and drop images directly into the input line to apply image processing functions
Unique to Mathematica -
Integrated environment for interactive visual workflow
C, C++, and other languages require you to switch between a graphical window and text input to visualize and process images
Using built-in filtering functions for feature detection
A custom interactive tool for thresholding gray-level images
Medical imaging specific capabilities:
- Efficient and powerful programmability for batch processing of images, interpreting proprietary data formats, quickly prototyping new image processing algorithms, and more »
- Binary, morphological, and other image segmentation algorithms for identifying shapes and regions, along with functions for shape and color analysis of image features »
- Mathematical morphology transforms and analysis, including finding branch points, skeletons, distance transforms, and more »
- Immediate detection or extraction of features such as edges, corners, and general keypoints for registering and comparing images »
- State-of-the-art linear and nonlinear image processing filters for smoothing, sharpening, removing noise, and more »
- Thousands of built-in functions for processing digital image intensity and color data »
- Calculus and linear algebra functions to solve differential geometry problems such as edge detection and curvature calculations
- Import, export, and convert hundreds of formats, including DICOM, FITS, and HDF »
- Easily build interactive interfaces to instantly visualize the effects of image manipulations like adjusting contrasts, enhancing edges, or applying filters »
- Support for GPU computation with CUDA or OpenCL, including built-in functions for pixel operations, morphological operators, and image convolution and filtering
- Discrete or continuous high-performance wavelet analysis for thresholding and visualizing in any dimension »
- Histograms, array plots, and list density plots to visualize image data »
- Connect to Java image processing libraries, or integrate with existing C/C++ code












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