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Supervised Automation of Cell Counting in Confocal Microscopic Cochlear Imaging Datasets Using Macro in Imaris

Rahman, M. T.; Khan, N. A.; Mokbul, M. I.; Razu, I.; Fatima, S. M.; Lira, S. S.; Garcia, C.; Eckard, P.; Hansen, M. R.

2024-07-24 immunology
10.1101/2024.07.24.604970 bioRxiv
Show abstract

Analyzing confocal microscopic data of biological samples using the Imaris software poses challenges due to its time-consuming nature involving tedious multiple steps and possibility of human errors. Here, we developed a supervised automation protocol to minimize manual input in cell and spot counting on confocal images obtained from mouse cochlear sections. The protocol increases efficiency by incorporating image recognition and object-oriented macros. Moreover, the protocol being adaptable allows scientists in diverse other fields to customize it for their specific needs. Graphical Abstract O_FIG O_LINKSMALLFIG WIDTH=200 HEIGHT=196 SRC="FIGDIR/small/604970v1_ufig1.gif" ALT="Figure 1"> View larger version (64K): org.highwire.dtl.DTLVardef@11b4aa0org.highwire.dtl.DTLVardef@c08c7dorg.highwire.dtl.DTLVardef@1479b59org.highwire.dtl.DTLVardef@280227_HPS_FORMAT_FIGEXP M_FIG C_FIG

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"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.