# Large-Scale Permanent Slide Imaging and Image Analysis for Diatom Morphometrics
## 4 Discussion
Accordingly, it would be thinkable to design an imaging/image analysis workflow where diatom slides are scanned over their whole area using a high-resolution oil immersion objective directly. This is indeed possible (and we have tested the procedure) but causes two difficulties: One is an enormous increase in storage capacity required to save the images. To capture the same physical surface area of a slide, roughly 10 times as many images captured by a high-resolution 63\(\times\) objective are necessary when compared to a 20\(\times\) objective. The difference is almost 40-fold when comparing the 63\(\times\) with a 10\(\times\) objective. In addition, the probability of individual diatom frustules not being captured fully on any single field-of-view image increases, hampering downstream analyses. This can in principle be helped by increasing the overlap between neighbouring fields-of-view, but to ensure that most frustules are captured fully in at least one field-of-view, the overlap between neighbouring images should be in the range of the size of the largest frustules in a sample, which is substantial. Taking 64 um, a not uncommon diatom size, as an example (this matches the overlap between neighbouring fields-of-view in our 20\(\times\) pre-scan): this corresponds to around 627 pixels in images captured at 63\(\times\) objective magnification. A full field-of-view image has 1360 \(\times\) 1024 pixels, i.e., the necessary overlap would correspond to almost half the image width and over 60% of image height. This leads to a further substantial increase of storage capacity, due to the fact that more images are required to capture the same slide area. Besides an increase in storage space requirements by more than an order of magnitude, processing time for downstream steps is also increased in a similar manner. Due to these complications, we finally adopted a two-step imaging procedure which was previously suggested and tested by the ADIAC project [4]. This consists of a low magnification area scan, followed by an image analysis step locating diatom frustules in the images, and by a high-resolution multiple focal planes imaging limited only to slide positions where objects of interest (frustules) were located (see Figure 1 steps 2-6). This procedure keeps storage space requirements relatively low while still allowing high precision of morphometric characterization. In order to be able to implement this workflow, software functionality for exporting outline point coordinates of objects found from SHERPA and importing these into virtual slides in the VSViewer software was developed in communication with Metasystems GmbH. **User efforts:** By all efforts at automation and supporting high throughput analyses, the quality of final results from this workflow can be substantially improved by human intervention at multiple steps of the workflow. Although in some situations it can be satisfactory to receive a subsample of diatom valves of interest in a defined slide area, there are also use cases when it is important to not miss (m)any objects of interest (quantitative counts). Also, diatom valves representing taxa of interest cannot be differentiated from other species (in the case of taxon-specific analyses), and from other types of objects commonly occurring on diatom slides (like sediment particles or unidentifiable fragments of broken diatoms) at a 100% accuracy and specificity. Furthermore, segmentation can be misled by touching or overlapping objects, minor fractures in valves or other anomalies. The workflow using slide scanning and SHERPA allows a fine scale control to address these issues. After the first slide scan generating an overview at low objective magnification, the target objects located by SHERPA can be manually checked and remaining non-diatom objects sorted out before further processing.