In this post I will demonstrate SimpleITK, an abstraction layer over the ITK library, to segment/label the white and gray matter from an MRI dataset. I will start with an intro on what SimpleITK is, what it can do, and how to install it. The tutorial will include loading a DICOM file-series, image smoothing/denoising, region-growing…
As Python has gained a lot of traction in the recent years in Data Science industry, I wanted to outline some of its most useful libraries for data scientists and engineers, based on recent…
Great reference with many open-source useful plotting and visualization tools Over the years many different plotting modules and packages have been developed for Python. For most of that time there was no clear favorite package, but recently matplotlib has become the most widely used. Nevertheless, many of the others are still available and may suit your tastes or needs better. Some of these are interfaces to existing plotting libraries while others are Python-centered new implementations.
News: all of the few remaining calls to scipy have been replaced with calls to numpy. Versions 0.1.8 and above do not require scipy as a dependency. Introduction This library provides Python functions for agglomerative clustering. Its features include * generating hierarchical clusters from distance matrices * computing distance matrices from observation vectors * computing statistics on clusters * cutting linkages to generate flat clusters * and visualizing clusters with dendrograms. The interface is very similar to MATLAB's Statistics Toolbox API to make code easier to port from MATLAB to Python/Numpy. The core implementation of this library is in C for efficiency.
This library provides Python functions for agglomerative clustering. Its features include * generating hierarchical clusters from distance matrices * computing distance matrices from observation vectors * computing statistics on clusters *