Abstract

The aim and objectives of this study were as follows: (i) to perform automated segmentation of knee thermal image using the regional isotherm-based segmentation (RIBS) algorithm and segmentation of ultrasound image using the image J software; (ii) to implement the RIBS algorithm using computer-aided diagnostic (CAD) tools for classification of rheumatoid arthritis (RA) patients and normal subjects based on feature extraction values; and (iii) to correlate the extracted thermal imaging features and colour Doppler ultrasound (CDUS) features in the knee region with the biochemical parameters in RA patients. Thermal image analysis based on skin temperature measurement and thermal image segmentation was performed using the RIBS algorithm in the knee region of RA patients and controls. There was an increase in the average skin temperature of 5.94% observed in RA patients compared to normal. CDUS parameters such as perfusion, effusion and colour fraction for the RA patients were found to be 1.2 ± 0.5, 1.8 ± 0.2 and 0.052 ± 0.002, respectively. CDUS measurements were performed and analysed using the image J software. Biochemical parameters such as erythrocyte sedimentation rate (ESR) and C-reactive protein (CRP) showed significant positive correlation with the thermal imaging parameters. The CDUS parameters such as effusion, perfusion and colour fraction correlated significantly with the clinical and functional assessment score. According to the results of this study, both infrared (IR) thermal imaging and CDUS offer better diagnostic potential in detecting early-stage RA. Therefore, the developed CAD model using thermal imaging could be used as a pre-screening tool to diagnose RA in the knee region.

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