Motion tracking in infrared imaging for quantitative medical diagnostic applications

Abstract

In medical applications, infrared (IR) thermography is used to detect and examine the thermal signature of skin abnormalities by quantitatively analyzing skin temperature in steady state conditions or its evolution over time, captured in an image sequence. However, during the image acquisition period, the involuntary movements of the patient are unavoidable, and such movements will undermine the accuracy of temperature measurement for any particular location on the skin. In this study, a tracking approach using a template-based algorithm is proposed, to follow the involuntary motion of the subject in the IR image sequence. The motion tacking will allow to associate a temperature evolution to each spatial location on the body while the body moves relative to the image frame. The affine transformation model is adopted to estimate the motion parameters of the template image. The Lucas–Kanade algorithm is applied to search for the optimized parameters of the affine transformation. A weighting mask is incorporated into the algorithm to ensure its tracking robustness. To evaluate the feasibility of the tracking approach, two sets of IR image sequences with random in-plane motion were tested in our experiments. A steady-state (no heating or cooling) IR image sequence in which the skin temperature is in equilibrium with the environment was considered first. The thermal recovery IR image sequence, acquired when the skin is recovering from 60-s cooling, was the second case analyzed. By proper selection of the template image along with template update, satisfactory tracking results were obtained for both IR image sequences. The achieved tracking accuracies are promising in terms of satisfying the demands imposed by clinical applications of IR thermography.

Heat transfer model for deep tissue injury: a step towards an early thermographic diagnostic capability

“…Our computational thermal modeling results show that tissue ischemia and inflammation can be manifested as skin surface temperature decrease and increase, respectively. Coupling inverse reconstruction techniques to surface temperature data obtained by IR imaging [ 34 , 35 ], key parameters of the DTI lesion, such as dimensions, depth, metabolic heat generation and blood perfusion rates can be estimated [ 36 ], which is the subject of our current research efforts. The long term goal of our study is to relate thermographic scan information with key physiological changes in the tissue to allow clinicians to detect DTI in early stages and to provide necessary intervention to mitigate its progression.…”

Skin Cancer Detection Using Infrared Thermography: Measurement Setup, Procedure and Equipment

“…Çetingül et al [12,[79][80][81][82][83][84][85][86] developed a transient thermal imaging system to accurately measure temperature differences on the skin surface to aid in the detection and diagnosis of metabolically active or malignant skin lesions. Cheng et al [87][88][89][90][91] optimized the measurement method, skin cooling, and motion tracking of the thermal imaging system developed by Çetingül. Godoy et al [9,76] proposed a standardized detection theory using dynamic thermography to detect the most common types of skin cancer.…”

Inverse method for quantitative characterisation of breast tumours from surface temperature data

“…The IR imager can be combined with a 3D imager, such as the Microsoft Kinect. As shown by Cheng [34], mapping 2D temperature data onto a 3D surface mesh generated by Kinect increases measurement accuracy and should be considered for clinical implementation. The geometry of the breast is not hemi-spherical and the COMSOL model can be adjusted to accommodate the exact shape when data are available.…”

“…The solution converged to the correct solution for all three initial guesses, with negligible errors (Table 4). Case 1 took the highest number of iterations to converge (34) and case 3 the least number of iterations Figure 9. Thermal recovery temperature profile of a point directly above the tumour corresponding to h 0 .…”