Collection

The Binary Pattern Dictionary Learning (BPDL) package is suitable for image analysis on a set/sequence of images to determine an atlas of a compact region. In particular, the application can be maping gene activation accross many samples, brain activations in a time domain, etc.

BIRL stands for "Benchmark on Image Registration methods with Landmark validation". BIRL is a cross-platform framework for comparison of image registration methods with landmark validation (registration precision is measured by user landmarks). The project contains a set of sample images with related landmark annotations and experimental evaluation of state-of-the-art image registration methods.

Some key features of the framework:

• automatic execution of image registration of a sequence of image pairs
• integrated evaluation of registration performances using Target Registration Error (TRE)
• integrated visualization of performed registration
• running several image registration experiment in parallel
• resuming unfinished sequence of registration benchmark
• handling around dataset and creating own experiments
• rerun evaluation and visualisation for finished experiments

Collection of several basic standard image segmentation methods focusing on medical imaging. In particular, the key block/applications are (un)supervised image segmentation using superpixels, object centre detection and region growing with a shape prior. Besides the open-source code, there is also a few sample images.

This component convolves the image with maximum filter. Each voxel is set to the maximum value of its neighborhood. The neighborhood is defined by a kernel, which has a diameter of 3 voxels.

A set of ImageJ Built-in Macro Functions used to perform operations on the ImageJ platform.