Efficient cytoplasmic cell quantification using a semi-automated FIJI-based tool
Lucas Unger1, Ulrik Larsen2, Shayla Sharmine2
1Mohn Research Center for Diabetes Precision Medicine, Department of Clinical Science, Faculty of Medicine, University of Bergen, Glasblokkene 1, Haukelandsbakken 15, 5009, Bergen, Norway. lucas.unger@uib.no.
Abstract:
Quantification of subcellular structures such as nuclei and cytoplasmic proteins using staining methods based on fluorescent dyes or fluorescently tagged antibodies are widely used in scientific research. Accurate high-throughput quantitation of these assays can be time consuming and challenging. Here, we present our FIJI based Semi-Automated counting Macro termed SAM, and we validate its accuracy against manual counting and other automated counting methods. By introducing this automated quantification tool, we aim to contribute to the ongoing efforts to enhance the reliability, efficiency, and standardization of immunostaining analysis in the field of diabetes research and beyond.


