A Cluster Validity Index-Based Objective Criteria for Aesthetic Evaluation of Periorbital Treatment

Dark circles and pigmentation around the eyes are common reasons people see dermatologists. An effective assessment of the severity of infraorbital color and texture differences is critical for determining appropriate treatment. Evaluation of the visual severity of cases is mostly based on visual inspection. Treatment efficiency is often measured using patient questionnaires in many cases. The subjectivity of assessments may lead to a prolonged healing process, misdiagnosis, and excessive use of drugs or chemicals.

In this study, a computer-aided objective evaluation approach was proposed for grading periorbital facial rejuvenation. This approach is based on the analysis of numerical features extracted from different facial regions in digital images. Healing was objectively graded by evaluating data clusters formed using the extracted features. Accordingly, an increase in the visual similarity between paired facial regions is accepted as an indicator of healing, which directly affects the form of data clusters. An intracluster validity index was measured to evaluate the clusters as dense and well separated. A total of 144 facial regions were extracted and examined, and the automatically calculated grades were compared with expert evaluations.

The cosmetic effects of the experimental drug were evaluated during the experiments, and expert grades were accepted as the ground truth. The results show that the proposed automated grading approach can evaluate rejuvenation with an accuracy of up to 0.91 accuracy in the upper orbital region.

This study concluded that the proposed data-clustering-based approach is promising and can be functional without any special instruments.