Development of a Robust Photogrammetric Metrology System for Monitoring the Healing of Bedsores

Abstract

A three‐camera close range photogrammetric system for robust and precise measurement of bedsores has been designed and constructed. MEDPHOS (MEDical PHOtogrammetric System) consists of three synchronised cameras with convergent optical axes. A light projector is fixed in the centre of the rig that holds the cameras. A special dot pattern is projected onto the surface to be measured, to compensate for the lack of natural texture on the wound surface. The proposed algorithm consists of the following steps: the cameras and projector are calibrated so that all interior and exterior parameters are known; tailored image segmentation procedures are developed and applied for the detection of the projected pattern dots from the uneven background of the images using morphologic operators; and watershed transformation is used to tackle the problem of overlapping pattern dots. To reduce the effects of non‐uniform illumination and specular reflection of light due to humidity (often the case with wounds), a homomorphic transformation is developed and applied to the images. After segmentation of the images, a connected‐component labelling procedure is used to establish the points for matching. The centroids of these components were precisely calculated. Intensity‐based image matching has been tested without yielding satisfactory results due to the significant deviation from the Lambertian reflection assumption used for solving the correspondence problem. This problem is reliably solved by developing a new algorithm based on geometric constraints that allow feature‐based matching and do not need approximate values of the location of the targets in the images. This robust three‐focal constraint is found to be very effective for matching provided the necessary conditions for the system configuration are met. Auxiliary photometric constraints together with the calibrated projector (which is treated like an active camera) also serve as additional sources of information for reducing the number of remaining ambiguities and checking the consistency of the results. Almost all of the required biometric information can be obtained rapidly, robustly and easily using MEDPHOS. Experimental results showed the effectiveness of the proposed technique.

Imaging technologies applied to chronic wounds

“…During the 1990's, most of the work used digital images of wounds to find a reliable difference between injured and non-injured skin using color image processing and active contour models. Between 1998 and 2005, several prototypes attempted to monitor 3D characteristics of a wound: structured light techniques [18,24], photogrammetry [19], an industrial 3-D digitizer [7] or a hand-held scanner [14]. All these prototypes were cumbersome and too expensive for routine care in clinics.…”

“…The most typical chronic wounds are pressure, venous and diabetic ulcers, which mainly affect geriatric population, or patients who have lost totally or partially their capability of mobility [18]. Pressure applied to a particular area for a long period of time causes decomposition and necrosis of subcutaneous tissue, fat and muscle [19,30]. In Europe, it is estimated that over 2 millions of patients suffer from pressure ulcers [30].…”

Wound Healing Assessment Using Digital Photography: A Review

“…Finally, the volume of the wound, the space sandwiched between the measured surface of the wound and the original healthy skin surface, was calculated [49]. Another research team worked on the same setting with a novel strategy in characterizing the point correspondences along with their performance evaluation resulted in 96.8% robust 3D point reconstruction [39]. Apart from high accuracy level, it failed to measure the moist wounds with flat surface due to presence of reflection.…”

“…Digital photo planimetry has become increasingly popular for wound healing assessment wherein series of well-obtained digital images taken from the same region of an ulcer along with dimensional measurements can be applied as a yardstick to monitor the effectiveness of a treatment strategy [3,4,[39][40][41]. In the context of wound's perimeter, area, and volume measurement, delineation in which details of the surrounding area is isolated from the wound information, is one the most important image processing steps; however, there is no single algorithm in existence that works perfectly for all types of wounds due to "the nature of the wounds".…”

“…These approaches increase the rate of contamination; and are inaccurate with error rate 10-40% and 5-15% for depth estimation using the cotton tips and wound moulds, respectively [46][47][48]. Several approaches tried to develop non-invasive volume measurement applying wound 3D reconstruction including photogrammetry [39,49], structured light analysis [4,17,34,50], and industrial 3D digitiser [18,51].…”