Feature Extraction from Segmentations of Neuromuscular Junctions

TL;DR

This paper introduces an algorithm for extracting morphological features from segmented neuromuscular junction images, enabling analysis of features not detectable by traditional segmentation methods.

Contribution

The paper presents a novel algorithm specifically designed to extract morphological features from neuromuscular junction segmentations, with an interface for parameter tuning.

Findings

Effective extraction of morphological features demonstrated.

Algorithm enhances analysis of neuromuscular junctions.

Provides a user-friendly interface for parameter adjustment.

Abstract

Segmentations are often necessary for the analysis of image data. They are used to identify different objects, for example cell nuclei, mitochondria, or complete cells in microscopic images. There might be features in the data, that cannot be detected by segmentation approaches directly, because they are not characterized by their texture of boundaries, which are properties most segmentation techniques rely on, but morphologically. In this report we will introduce our algorithm for the extraction of suchlike morphological features of segmented objects from segmentations of neuromuscular junctions and its interface for informed parameter tuning.