Medical Data Segmentation Toolkit

The current version is 1.1.1.

MDSTk is distributed under a public license which permits modification and distribution of the toolkit. For more information, see the full text of the license.

• Multiplatform toolkit running on Linux and Windows platform, supported compilers are
1. GCC 3.2+ compiler on linux systems,
2. MinGW compiler (windows port of GCC compiler),
3. MS Visual C++ 7.1+ compiler on windows systems.
• Uses the excellent CMake (Cross-platform Make) build system.
• Simple modular architecture.
• 2D/3D image processing library including
• number of convolution filters,
• edge detectors (e.g. 3D canny edge detector),
• FFT,
• segmentation algorithms (thresholding, RG, FCM, Watersheds, etc.),
• texture analysis (LBP features).
• Experimental support for the OpenCV library. You can can take advantage of both libraries.
• Math library based on the Eigen + UMFPACK libraries providing static/dynamic vectors and matrices, sparse matrices, etc. including linear algebra routines (e.g. eigenvalues and eigenvectors problem).
• Some advanced algorithms implemented:
• Fuzzy c-Means clustering,
• optimization of GMMs (Gaussian Mixture Models) using Expectation-Maximization algorithm (EM algorithm).
• Several image/slice formats supported: DICOM, JPEG and PNG.
• Low-level vector graphics library for effective handling of polygonal surface models and tetrahedra meshes.
• Benefit from templated C++ code, e.g. speed and scalability.
• Interesting programming techniques used, such as smart pointers, reference counting, singletons, serialization, iterators and so on.
• Inter-module communication over channels implemented via files, named/unnamed pipes, shared memory (and network in future).
• Multiplatform system library encapsulating threads, mutexes, critical sections, timers and etc.
• Source code documentation generated using Doxygen.
• Public BSD-like license, all source codes available.

Running module from command line:

-i	Specification of a module input channel. Channel is described with a string of the form medium[:attrib1[:attrib2[...]]] Allowed medium types are stdio, file, pipe and shm. First one has no attributes, file and pipe have only one attribute - the filename. Communication over shared memory is not elementary (see documentation).
-o	Output channel specification same as above.
-log	Option selects a module log type. Allowed values are null for no logging, stderr for logging to the stderr, file means logging to a file and both sets logging to the both stderr and file.
-h	Shows more detailed help.

Samples:

1. mdsLoadJPEG < temp/berounka.jpg | mdsSliceInfo or
   mdsLoadJPEG -i file:temp/berounka.jpg | mdsSliceInfo
   - Reads input image and prints basic information about it.

2. mdsLoadJPEG < temp/berounka.jpg >berounka.slc
   - Reads input image and saves it in the MDSTk format.

3. mdsLoadDicom < data/dicom/80.dcm | mdsSliceRange -auto | mdsSliceView
   - Loads image data in DICOM format, changes pixel value range from 12-bit (density medical data) to the 0..255 (8-bit grayscale image) and shows it.

4. mdsLoadDicom < data/dicom/80.dcm | mdsSliceFilter -filter gaussian -sigma 1.0 | mdsSliceRange -auto | mdsSliceView
   - Gaussian smoothing of the input image.

Libraries description:

libBase	Base classes, templates and functions (singletons, small objects, type traits, logging, ...).
libMath	Static/dynamic vectors, matrices, random numbers, etc.
libImage	Image and volume data processing functions.
libImageIO	Loading and saving of image data from/to various formats.
libSystem	Multiplatform library encapsulating threads, mutexes, critical sections, timers and etc.
libModule	I/O channels, object serialization, ...
libVectorEntity	Vector graphics library (polygonal surfaces, tetrahedral meshes and so on).

Base modules:

mdsCreateSHM	Creates and handles a block of shared memory.
mdsLoadDicom	Reads an image in the DICOM format from the input channel and converts it to the MDSTk native format. Typical output is a density 12-bit grayscale image, called slice in medical imaging.
mdsLoadJPEG	Reads and converts any JPEG image.
mdsLoadPNG	Reads and converts any PNG image.
mdsMakeVolume	Module makes density volume data (3D image) from several input slices.
mdsRGBImage2Slice	Converts input RGB image to slice.
mdsRGBImageView	Shows input RGB image in OpenGL window.
mdsSaveJPEG	Converts input slice to the JPEG image format.
mdsSavePNG	Converts input slice to the PNG image format.
mdsSliceAffineTransform	Affine geometric image transform.
mdsSliceBlending	Merges two images/slices.
mdsSliceCornerDetector	Provides basic image corner detection methods (Harris and Susan).
mdsSliceCut	Keeps values of a specified interval of pixels unchanged, remaining ones are set to zero.
mdsSliceEdgeDetector	Advanced edge detection algorithms (e.g. Canny edge detector).
mdsSliceFFT	This sample module computes two-dimensional DFT of an input slice.
mdsSliceFilter	Provides several image filtering functions such as Median, Sobel and Prewit operators, Gaussian smoothing and many others.
mdsSliceHistEqualization	Histogram equalization.
mdsSliceHistogram	Shows histogram of input slice.
mdsSliceInfo	Shows information about input slice.
mdsLBPCompare	Compares LBP histograms of two images.
mdsLBPExtract	Extracts LBP codes from an image.
mdsLBPHistogram	Estimates normalized LBP histogram of an image.
mdsSliceOpticalFlow	Estimates optical flow between two images using the Lucas-Kanade method.
mdsSliceRange	Extends a given pixel value interval to specified range (linear interpolation).
mdsSliceSubsampling	Module demonstrates use of the Gaussian pyramid for image subsampling.
mdsSliceSeg	Sample slice segmentation module.
mdsSliceSegHT	Slice segmentation based on histogram thresholding.
mdsSliceSegRG	Simple region growing segmentation algorithm.
mdsSliceSegEM	Pixel-based segmentation using GMMs (Gaussian Mixture Models and well known Expectation-Maximization algorithm.
mdsSliceSegFCM	Another pixel-based segmentation algorithm. It uses the fuzzy C-means clustering algorithm.
mdsSliceSegWatersheds	Watersheds-based image segmentation.
mdsSliceTresholding	Simple pixel value tresholding.
mdsSliceView	Visualizes input slice using GLUT and OpenGL.
mdsVolumeBlending	Merges two volumes.
mdsVolumeCut	Leaves a specified interval of voxel values unchanged and sets remaining ones are set to zero.
mdsVolumeFilter	Several volume filtering functions (Median, Sobel operator, etc.)
mdsVolumeEdgeDetector	3D Canny edge detection algorithm.
mdsVolumeHistEqualization	Volume data histogram equalization.
mdsVolumeHistogram	Shows volume data histogram.
mdsVolumeInfo	Prints information about input volume.
mdsVolumeLandmarkDetector	Experimental algorithms for detection of landmark points in volume data.
mdsVolumeRange	Extends a given voxel value interval to specified range.
mdsVolumeSeg	Sample volume segmentation module.
mdsVolumeSegEM	Voxel-based segmentation using GMMs (Gaussian Mixture Models and well known Expectation-Maximization algorithm.
mdsVolumeSegFCM	Another voxel-based segmentation algorithm. It uses the fuzzy C-means clustering algorithm.
mdsVolumeSegHT	Volume segmentation based on histogram thresholding.
mdsVolumeSegRG	Region growing segmentation of volume data. Very slow implementation! Should be remade in future.
mdsVolumeSlit	Splits input volume into several slices.
mdsVolumeTresholding	Simple voxel value tresholding.
mdsVolumeView	Reads input volume and visualizes it using GLUT and OpenGL.

How can you build the documentation? First, install the Doxygen system (http://www.doxygen.org/) and optionaly the Graphviz package (http://graphviz.org/) for drawing graphs such as the class diagram.

If you use Makefiles and 'make' command to compile the toolkit just type

> make doc

Even easier it is under MS Visual Studio. Open the generated solution choose project 'ALL_DOC' and compile it. This will make Doxygen documentation for you. You will find it in your build directory.