ArXiv Preprint
Melanoma is the most lethal type of skin cancer. Patients are vulnerable to
mental health illnesses which can reduce the effectiveness of the cancer
treatment and the patients adherence to drug plans. It is crucial to preserve
the mental health of patients while they are receiving treatment. However,
current art therapy approaches are not personal and unique to the patient. We
aim to provide a well-trained image style transfer model that can quickly
generate unique art from personal dermoscopic melanoma images as an additional
tool for art therapy in disease management of melanoma. Visual art appreciation
as a common form of art therapy in disease management that measurably reduces
the degree of psychological distress. We developed a network based on the
cycle-consistent generative adversarial network for style transfer that
generates personalized and unique artworks from dermoscopic melanoma images. We
developed a model that converts melanoma images into unique flower-themed
artworks that relate to the shape of the lesion and are therefore personal to
the patient. Further, we altered the initial framework and made comparisons and
evaluations of the results. With this, we increased the options in the toolbox
for art therapy in disease management of melanoma. The development of an
easy-to-use user interface ensures the availability of the approach to
stakeholders. The transformation of melanoma into flower-themed artworks is
achieved by the proposed model and the graphical user interface. This
contribution opens a new field of GANs in art therapy and could lead to more
personalized disease management.
Lennart Jütte, Ning Wand, Bernhard Roth
2023-03-16
