SHERPA: an image segmentation and outline feature extraction tool for diatoms and other objects

Abstract

BackgroundLight microscopic analysis of diatom frustules is widely used both in basic and applied research, notably taxonomy, morphometrics, water quality monitoring and paleo-environmental studies. In these applications, usually large numbers of frustules need to be identified and/or measured. Although there is a need for automation in these applications, and image processing and analysis methods supporting these tasks have previously been developed, they did not become widespread in diatom analysis. While methodological reports for a wide variety of methods for image segmentation, diatom identification and feature extraction are available, no single implementation combining a subset of these into a readily applicable workflow accessible to diatomists exists.ResultsThe newly developed tool SHERPA offers a versatile image processing workflow focused on the identification and measurement of object outlines, handling all steps from image segmentation over object identification to feature extraction, and providing interactive functions for reviewing and revising results. Special attention was given to ease of use, applicability to a broad range of data and problems, and supporting high throughput analyses with minimal manual intervention.ConclusionsTested with several diatom datasets from different sources and of various compositions, SHERPA proved its ability to successfully analyze large amounts of diatom micrographs depicting a broad range of species. SHERPA is unique in combining the following features: application of multiple segmentation methods and selection of the one giving the best result for each individual object; identification of shapes of interest based on outline matching against a template library; quality scoring and ranking of resulting outlines supporting quick quality checking; extraction of a wide range of outline shape descriptors widely used in diatom studies and elsewhere; minimizing the need for, but enabling manual quality control and corrections. Although primarily developed for analyzing images of diatom valves originating from automated microscopy, SHERPA can also be useful for other object detection, segmentation and outline-based identification problems.

Large-Scale Permanent Slide Imaging and Image Analysis for Diatom Morphometrics

“…Image analysis and object measurement is realized by our software SHERPA (version 1.1c) [5], which is a freely available Microsoft Windows software developed specifically for diatom morphometry. SHERPA can apply a set of different image processing methods for detecting objects in light microscopic images, and compares their contour outline to a set of shape templates to identify objects of interest.…”

“…However, the analysis of large image sets, as they can easily be produced by slide scanning microscopes, has remained challenging for most diatomists not trained in image analysis. To fill this gap, we developed SHERPA, a user-friendly software tool conducting segmentation of such images and morphometric characterization of objects of interest [5]. This tool incorporates some of the ideas and experiences reported previously [4,6], and contributes a number of novel ideas to support quick but highly precise morphometric characterization of diatom outlines.…”

Automated Diatom Classification (Part A): Handcrafted Feature Approaches

“…It is out of the scope of this paper to present all of the segmentation methods; for further details, the reader is referred to the reviews mentioned in Section 1 [12,13,18]. In this work, we present an automatic method used to do an initial quick segmentation, which required visual supervision afterward to include only the correct segmented diatoms.…”

“…Another attempt to describe the morphology and geometry of diatoms is the work of Kloster et al [13], who developed a system that allows the segmentation and feature extraction from diatom contours, although it does not provide textural information about the frustule. As mentioned by Pappas et al [12], two areas of study may be identified with regard to the methods used in diatom research, namely shape analysis and pattern recognition.…”

A Tuning Method for Diatom Segmentation Techniques

“…These techniques are usually used as steps in the analysis and identification of diatoms and the detection of other phytoplankton organisms [7]. Figure 5 shows nine images taken from the employed dataset [12].…”