How Automated Melanoma
Diagnosis Works
Images
of skin lesions are taken using a technique called surface microscopy.
The area of interest around the lesion is coated with a film of oil, a piece
of glass is pressed onto the area, and a colour picture is taken through the
glass with a low-power microscope. The lesion attributes are then analysed
using image analysis techniques. Figure 1 shows the images of four different
lesions. Each image is about 9 millimetres high by 14 millimetres wide.
Figure 1: Four skin lesions
Images taken using surface microscopy aren't perfect: hair and bubbles in the oil can be
seen. These features could perturb the diagnosis and so must be removed by the image
analysis software. Also the boundary of the lesion must be detected, as shown in Figure 2.
The lesion boundaries are in yellow; the hairs and other unwanted features are in green
Figure 2: Detected lesion boundaries, hairs and bubbles
Having found the boundary of the lesion, various attributes of the lesion must be
measured. These permit us to classify it as melanoma or not. A reliable diagnosis cannot
be deduced from colour information alone. In particular, notions like the symmetry
and the regularity of the lesions are very important. To illustrate the importance of these factors, figure 3 shows an example where lesion (e)
is a melanoma and lesion (f) is not. No colour information can help discriminate
between these two lesions. However, lesion (e) can be recognised as a melanoma on
the basis of additional features.
 |
 |
| (e) |
(f) |
Figure 3: Lesions identified as (e) melanoma and (f)
non-melanoma.
Classification Accuracy In the
following study, SolarScan was
shown to have comparable or superior sensitivity and specificity in
comparison with clinicians. The sensitivity and specificity figures for
SolarScan and a range of clinicians with varying levels of expertise in the
diagnosis of melanoma are shown in the table below.
S. Menzies,
L.
Bischof, H. Talbot, et al. The Performance of SolarScan: An
Automated Dermoscopy Image Analysis Instrument for the Diagnosis of Primary
Melanoma. Archives of Dermatology, 141(11):1388-1396, November
2005.
| Diagnostician |
Sensitivity (%) |
Specificity (%) |
| SolarScan |
85 |
65 |
| Dermoscopy experts |
90 |
59 |
| Dermatologists |
81 |
60 |
| Trainee Dermatologists |
85 |
36 (p=0.006) |
| General Practitioners |
62 |
63 |
Return to the melanoma
identification page.
For more information contact
Pascal Vallotton. |
