Construction of a New Data Set of Pleural Fluid Cytological Images for Research

Abstract

The limited availability of standardized datasets has hindered the implementation of artificial intelligence (AI) models in serous fluid cytology, particularly in pleural fluid analysis. In this paper, we present the construction of a dataset of pleural fluid cytology images. The objective is to generate a dataset of pleural fluid cytologic images validated by two pathologists and classified into five categories for cell diagnosis, which will be used to train AI models. As a methodology, the images represent pleural fluid cytology samples that have been prepared through medical procedures and transferred to slides, providing valuable information when evaluated under the microscope by medical specialists through cytological examination. We documented the entire process for building the pleural fluid cytological image dataset, from image capture, labeling, preprocessing, standardization, and uploading to public platforms. As a result, we obtained a pleural fluid cytology dataset based on the International System (TIS) criteria for reporting serous fluids, classifying samples into AUS, MAL, ND, NFM, and SFM. This dataset is intended to support medical research, deep learning applications in medical image analysis, and improved diagnostic methodologies.