About the Segmentation Tools

Segmentation, also known as classification or labelization, is the process of partitioning an image into multiple segments or sets of pixels that share certain characteristics. The main goal of segmentation is to simplify or change the representation of an image into something that is more meaningful and easier to analyze. In simple cases, environments may be well enough controlled so that the segmentation process reliably extracts only the parts that need to be analyzed further. In complex cases in which boundaries are indistinct, such as missing edges or a lack of contrast between foreground and background regions, segmentation can be more difficult. In either case it is important to understand that:

• There is no universally applicable technique that will work for all types of images.
• No segmentation technique is perfect.
• Post-processing, by smoothing noisy images or enhancing edges, can accelerate some segmentation tasks (see Image Filtering).

The following tools and options are available in Dragonfly for segmenting image data.

Thresholding… The options in the Range box on the ROI Tools panel allow you to define an intensity domain of image data values and then apply the selected range as a threshold segmentation (see Defining Intensity Ranges). Intensity domains are also applicable to other tools, such as the morphological operators and the ROI Painter tools.

ROI Painter tools… The tools on the ROI Painter panel are used for manual segmentation and for editing regions of interest and multi-ROIs (see ROI Painter).

Histographic segmentation… With this tool, you can quickly segment a dataset by selecting clustered data values, which will be propagated to all data points that meet the selection criteria. Regions of interest created in this manner can either be exported or expanded through a Watershed algorithm to fully segment the selected dataset (see Histographic Segmentation).

Segmentation Wizard… Dragonfly's Segmentation Wizard provides an easy-to-use, guided workflow for training deep learning and classical machine learning segmentation models for semantic segmentation (see Segmentation Wizard).

Machine Learning Segmentation… This advanced machine learning plug-in for image segmentation, provides an opportunity to train a classifier within a limited sample in an image so that it will learn how to segment the pixels of the whole dataset or other similar datasets (see Machine Learning Segmentation).

Deep Learning… Lets you create robust and reproducible segmentation results by training a deep model for semantic segmentation (see Deep Learning Tool).