A Review on Texture Feature Analysis of Chest Computed Tomography Images for Detection and Classification of Pulmonary Diseases Priya Sawant and R. Sreemathy Abstract Computer Aided Diagnostic systems developed to facilitate early detec- tion of pulmonary diseases have exploited texture features to identify radiological patterns on Chest Computed Tomography scans of patients. This paper reviews research studies that have done analysis of texture features to facilitate detection and classification of pulmonary diseases. First, texture and types of texture feature extraction techniques are discussed in brief. Comparison of performance metrics of machine learning-based classifiers used in conjunction with texture feature analysis is also presented. Published research works indicate high performance of second and higher-order statistical feature extraction methods. Support vector machine algo- rithm exhibits best performance in texture-based disease classification. Finally, we explore the challenges faced in texture analysis and potential future research paths in this domain. Keywords Texture analysis · Lung disease · Feature extraction · Classification · Machine learning · Pulmonary infection · Chest CT 1 Introduction A widely used feature extraction technique in Computer Aided Diagnostic (CAD) systems to detect and classify lung diseases is analysis of texture features of chest CT scans. Lungs are an essential part of the human respiratory system. Lung cancer, Chronic Obstructive Pulmonary Disease (COPD), Asthma, Interstitial Lung Disease (ILD), Tuberculosis (TB), and Severe Acute Respiratory Syndrome (SARS) are some of the major lung diseases affecting people across the globe [1]. Lungs are also vulner- able to infections caused by viruses, bacteria, and fungi, some of which are highly P. Sawant (B ) · R. Sreemathy SCTR’s Pune Institute of Computer Technology, Pune, India e-mail: priyasawant@mmcoe.edu.in R. Sreemathy e-mail: rsreemathy@pict.edu © The Author(s), under exclusive license to Springer Nature Singapore Pte Ltd. 2023 H. Sharma et al. (eds.), Communication and Intelligent Systems, Lecture Notes in Networks and Systems 686, https://doi.org/10.1007/978-981-99-2100-3_36 463