Comparing Segmentation Algorithms in Medical Diagnostics Using Thermal Imaging

In this study, thermal images have been categorized to obtain various segmented images. Based on the differentiation of various segmented algorithms. This is a non-invasive diagnostic technique that measures body heat emissions and helps make diagnosing easier by combining it with the patient's clinical data. The study explores the creative applications of thermal sensing with a focus on analyzing thermal pictures using sophisticated image segmentation algorithms using IR thermography in a medical context. Thermal imaging offers important insights into physiological processes. It can rapidly identify anomalies that are difficult to detect with conventional techniques, like inflation, tumors, or circulatory problems. Every algorithm possesses distinct benefits and drawbacks of its own. The purpose is to determine which techniques yield the most trustworthy and accurate segmentation outcomes. The final objective is to combine these segmented thermal pictures with the patient's clinical data to create a comprehensive diagnostic tool that will improve the precision of the medical diagnosis.