Segmentation of 3D images of plant tissues at multiple scales using the level set method

Background

Developmental biology has made great strides in recent years towards the quantification of cellular properties during development. This requires tissues to be imaged and segmented to generate computerised versions that can be easily analysed. In this context, one of the principal technical challenges remains the faithful detection of cellular contours, principally due to variations in image intensity throughout the tissue. Watershed segmentation methods are especially vulnerable to these variations, generating multiple errors due notably to the incorrect detection of the outer surface of the tissue.

Results

We use the level set method (LSM) to improve the accuracy of the watershed segmentation in different ways. First, we detect the outer surface of the tissue, reducing the impact of low and variable contrast at the surface during imaging. Second, we demonstrate a new edge function for a level set, based on second order derivatives of the image, to segment individual cells. Finally, we also show that the LSM can be used to segment nuclei within the tissue.

Conclusion

The watershed segmentation of the outer cell layer is demonstrably improved when coupled with the LSM-based surface detection step. The tool can also be used to improve watershed segmentation at cell-scale, as well as to segment nuclei within a tissue. The improved segmentation increases the quality of analysis, and the surface detected by our algorithm may be used to calculate local curvature or adapted for other uses, such as mathematical simulations.

     

Abnormal Sysmex XT‐2000iV DIFF scattergram in a cat with a prominent mastocytemia

A 2‐year‐old neutered male domestic shorthair cat was presented to the emergency service of the National Veterinary School of Toulouse (France) for acute vomiting and diarrhea with lethargy, inappetence, and adypsia for the past 48 hours. Complete blood counts were performed with the ProCyte DX at the emergency department and with the Sysmex XT‐2000iV at the laboratory 2 weeks later. The scattergrams from the two analyzers revealed similar unusual and abnormal dot plots. The Sysmex XT‐2000iV DIFF scattergram also showed no clear separation between different leukocyte populations. The eosinophil cluster was in an abnormal location compared with that of the “typical” location in a normal cat. A blood smear evaluation revealed the presence of numerous mast cells. Thus, we hypothesized that the Sysmex XT‐2000iV had detected the mast cell population, and this led to errors in the differential counts. To explore this hypothesis, we manually gated on the DIFF scattergram and performed a manual differential on the blood smear. With this new gating strategy, the Sysmex XT‐2000iV and manual differentials were similar. Thus, in the case of systemic mastocytosis, mast cells can be located between the lymphocyte, monocyte, and eosinophil clusters on scattergrams.     

Immunohistochemical characterization of a hepatic neuroendocrine carcinoma in a cat.

A hepatic mass was identified in a 5-year-old, female mixed-breed cat that died spontaneously after a clinical history of progressive emaciation, ptyalism, and persistent coryza. At necropsy, a 7-cm-diameter, yellow-brown, firm, multilobulated tumor was identified in the liver. Microscopically, the mass consisted of neoplastic cells arranged in small, closely packed nests within a thin fibrovascular stroma. These cells were of medium sized and polygonal, with fine argyrophilic cytoplasmic granules. Nuclei were predominantly round with finely stippled chromatin and indistinct nucleoli. Mitotic figures were numerous. Immunohistochemically, most of the neoplastic cells were immunoreactive for chromogranin A, neuron-specific enolase (NSE), and cytokeratin AE1/AE3 and weakly labeled for synaptophysin. The tumor was negative for glial fibrillary acidic protein (GFAP), vimentin, and cytokeratins 5, 6, 8, and 17. Vascular emboli and intrahepatic micrometastasis were also identified with chromogranin A. All these features were consistent with a hepatic neuroendocrine carcinoma and emphasized the importance of using a panel of antibodies to diagnose such rare tumors.     

Detection of circulating microfilariae in canine EDTA blood using lens-free technology: preliminary results

Dirofilaria immitis causes life-threatening heart disease in dogs, thus screening of dog populations is important. Lens-free technology (LFT) is a low-cost imaging technique based on light diffraction that allows computerized recognition of small objects in holographic images. We evaluated an algorithm capable of recognizing microfilariae in canine whole blood using the LFT. We examined 3 groups of 10 EDTA blood specimens, from dogs with microfilaremia (group A), healthy dogs (B), and dogs with hematologic modifications other than microfilaremia (C). The LFT analyzer photographed repeated series of 5 images of all samples. The algorithm declared a sample positive if a microfilaria was detected on ≥1, ≥2, or ≥3 of the 5 images of a series. Microfilariae were detected visually in the images in 9 of 10 cases in group A; no microfilariae were seen in the images from groups B and C. Of the 30 cases, there were 14, 4, and only 3 false-positives with the 1 of 5, 2 of 5, and 3 of 5 image cutoffs, respectively. There were no false-negatives, regardless of cutoff. LFT seems useful for detecting microfilaria and could have application in clinical pathology.