Name
Abstract | ||
|---|---|---|
Melanoma is the deadliest form of skin cancer. It mainly requires a visual diagnosis by dermatologists. However, a dermatologist's recognition of melanoma may be subject to errors and may take some time to diagnose correctly it. To this aim, in the last twenty years, Computer-Aided Diagnosis systems based on artificial vision are increasingly adopted to support dermatologists in the early diagnosis of melanoma. However, these systems exploits only a reduced set of parameters or they implement a melanoma classifier that tries to substitute the dermatologists, without supporting their experience in the classification of skin lesions. This paper proposes a mobile application for supporting the clinician decision in the diagnosis of melanoma directly in the dermatologist environment by using Augmented Reality technology. In particular, computer-generated perceptual information is added to the image of patient skin reporting the values of various parameters and the lesion classification based on deep learning approach for analyzing skin lesions and identifying melanoma. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1109/IV51561.2020.00018 | 2020 24th International Conference Information Visualisation (IV) |
Keywords | DocType | ISSN |
Image Analysis,Augmented Reality,Melanoma,Neural Network | Conference | 1550-6037 |
ISBN | Citations | PageRank |
978-1-7281-9135-5 | 0 | 0.34 |
References | Authors | |
0 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rita Francese | 1 | 0 | 0.68 |
| Maria Frasca | 2 | 0 | 1.01 |
| Michele Risi | 3 | 0 | 1.01 |
| Genoveffa Tortora | 4 | 0 | 0.34 |