# Infrared Thermal Imaging Analysis in Screening for Toddler's Fracture: A Proof-of-Concept Study
## 3 Results  
A typical infrared thermal image of a participant with a toddler's fracture is shown in an RGB format in Figure 2a. The participant was a 14-month male with a toddler's fracture of his right leg. The fracture was not detected by X-ray radiography on the first attendance to the hospital. The injured leg was put into a cast and the participant underwent another X-ray on the second visit, 10 days later. It was then confirmed as a toddler's fracture (non-displaced transverse right proximal tibial fracture). The infrared thermal image of the right leg was relatively warmer (brighter colour) as compared with the uninjured left leg. Although visual inspection of an infrared image (Figure 2a) may highlight temperature anomalies associated with an injury, image and data analysis are still required for a conclusive interpretation [12; 13]. The image process was carried out on the temperature image (matrix of temperature values) shown in Figure 2b (not on RGB images). Figure 3a,b show infrared thermal images for a male participant, aged 3 years and 9 months, admitted with an injury to the right leg, in an RGB format and as a temperature format, respectively. The participant had an X-ray radiograph on the first hospital visit, but a fracture could not be confirmed. The injured leg was put in a cast and X-rayed again two weeks later, when the absence of a fracture was confirmed. Figure 1: The averaging operation for non-fracture participants. As an illustration, a scatter plot of median, standard deviation, and mean temperature difference (i.e., the temperature difference between the injured and uninjured legs) is provided in Figure 4. The plot includes all eight participants with a fracture (shown as asterisks) and 31 participants without a fracture (shown as circles). Two distinct clusters were identifiable, representing fracture and not fracture groupings. Although most participants were correctly clustered, there were a few participants appearing in the wrong clusters. Figure 5 shows a scatter plot of median, standard deviation, and mean temperature difference illustrating the application of the averaging method (outlined in Figure 1) to the 31 participants without a fracture (represent by black circles) to reduce their number to 15 (shown by red asterisks). Table 3 shows the temperature difference between the injured and uninjured (conralateral) legs for the eight participants with a fracture and 15 averaged participants without a fracture. The maximum temperature measure showed a 60.2% difference between the injured legs resulting in a fracture and not fracture. Similarly, the mean temperature measure shows a 59.6% difference between the injured legs resulting in a fracture and not fracture. Figure 3: Infrared thermal image (**a**) RGB format, (**b**) temperature image of a participant diagnosed by an X-ray as not having a toddler’s fracture (right leg injury). The temperature image indicates the cropping of the ROI on the right leg. The uninjured left leg was similarly cropped. Figure 2: An example of an infrared thermal image for a participant diagnosed by X-ray to have a toddler’s fracture of the right tibia. (**a**) RGB format; (**b**) processed temperature image indicating the cropped region of interest on the right leg (the uninured left leg was similarly cropped). Figure 4: A scatter plot of median, standard deviation, and mean temperature difference between fractured (represented by asterisks) and uninured legs (represented by circles).