2D

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

jSLIC superpixels - is a segmentation method for clustering similar regions - superpixels - in the given image which are usually used for other segmentation techniques. The only two parameters are average (initial) size of each superpixel and rigidity parameter in range (0,1)

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 workflow processes a group of images containing cells with discernible nuclei and segments the nuclei and outputs a binary mask that show where nuclei were detected. It was developed as a test workflow for Neubias BIAFLOWS Benchmarking tool.