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This task is usually obstructed by cell conglomerates of various sizes.
Closer examination suggested that both of these tumor cell conglomerates were themselves organized into distinct microdomains.
Therefore, the here described procedure is untroubled also by densely packed cell conglomerates (see figure 6).
We here dealt with the problem of incorporating complex cell conglomerates into histological cell count cut-off studies.
Based on the target objects' area size it was classified into "single T cells" or "T cell conglomerates".
In this article we present such an algorithmic approach which yields robust and reliable estimations of cell densities in even in large cell conglomerates.
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For a "T cell conglomerate" its area was divided by the average area of a single T cell (51 µm2) to obtain an estimate of the underlying cell density yielding an estimated T cell number.
This type of response is believed secondary to infiltrating T-cell conglomerates around the tumors giving the radiographic appearance of greater tumor size and hence, progressive disease.
High magnification view demonstrated small cells conglomerated each other in the bovine bone group (c).
Specific explanations regarding image processing are therefore omitted here, because any implementation should somehow lead to the detection of single cells and aggregated cell clusters ("conglomerates").
Bone marrow was a cell-rich conglomerate with intervening empty areas from dissolved fat and few scattered thread-like structures.
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com