Mobile Application for Ulcer Detection
might be present. The segments were then
dilated to recover the foot area that might
have been lost because of the eroding process.
Now feet segments were considered as the
background, whereas the suspected hottest
region was the foreground. The hottest region
was extracted using another binary threshold
of 244 for the grayscale. Although the hottest
region has been identified, verification must
be applied to decide whether this was an
ulcerous region or not. The decision was
taken based on the temperature variation
between the suspected hottest region and the
normal feet region. The threshold values of
149 and 244 were selected after meticulously
studying various scenarios involved in early
detection of DFU such as shape, size, and
region of the suspected ulcerous region of
the foot by using the process as described in
the previous subsection. The threshold values
depict the suspected region with highest
variation in temperature as compared to the
rest of the foot. In addition, the normal feet
region was analyzed without the suspected
ulcer region. The mean temperature of both
regions was then calculated and prepared for
further analysis. For this, the radiometric data
that was previously saved was used, as the
mean temperature observed was only for the
pixels that depicted the required region. The
difference between both extracted segments
provided the needed outcomes to decide
whether the case was ulcerous, which was an
increase of more than 2.2 o C, or normal feet
temperature variations.
Usually to determine whether the foot is
ulcerous, the mean temperature of the feet
segment, which is represented without the
hottest region, is subtracted from the mean
temperature of the hottest region. The
24
Pedorthic Footcare Association | www.pedorthics.org
Mean Temperature Difference (MTD) is then
calculated. If the MTD is 2.2 o C less, the foot
is normal, and no ulcer is detected. However,
if the MTD is above 2.2 o C, then an ulcer is
present. Moreover, false positives and false
negatives results are obtained if the feet
region and the hottest region are below 25 o C,
or if the feet region and the hottest region are
above 50 o C.
This represents the worst-case scenario with
a maximum temperature that the human
foot can have. If either of these conditions is
triggered, then no ulcer is detected. This is
under the assumption that the background
is completely cold. On the other hand, the
BGR image was extracted from the original
thermal image. Upon reading the image,
OpenCV was set to output the image in the
BG R order representing the Blue, Green, and
Red channels. Colors were used to signify
the ulcerous region, if present. For example,
blue represented the foot devoid of ulcer
and red represented the ulcerous region.
The background of the thermal image was
removed from the BGR image to obtain only
the feet segment. This was done by first
converting the BGR to grayscale image. The
acquired image is shown in Fig. (5). The stand-
alone smartphone application automatically
applies the developed algorithms and threads
on the radiometric data to represent it as a
2D grayscale image. The image shown for
the user is a color image of a range from 0
to 255, which represents the variations of the
temperature on the acquired image between
the background and the feet (foreground).
Next, a threshold is applied to the greyscale
image to filter out the low values and set them
to zero. This works in the same way as a high
pass filter. The segmentation procedure is