Potential of the ImageJ software in the differentiation of various types of canine lymphadenopathies with fine needle aspiration cytology (FNAC)

Two-dimensional Quantitative Profiling of Cell Morphology with Serous Effusion by Unsupervised Machine Learning Analysis

“…The data obtained for nuclear morphometric features (diameter, circularity, area, and perimeter) revealed a significant difference between the control group and the hyperplasia and lymphoma groups. The cytology diagnosis technique used in this study was rapid, simple, and cheap and the assessment by image analysis software can increase diagnostic accuracy [32]. In 2015, Raghavan et al published two independent studies that discussed the use of ImageJ and three of its plug-ins to analyze the nuclear parameters in different kinds of carcinoma.…”

“…We used Fiji (ImageJ distribution focuses on biological image analysis) to calculate marked cells' 2D morphometric features [31,32]. These features are characterized by A c parameter and related A n parameter.…”