Name
Title | ||
|---|---|---|
Segmentation And Classification Of Cutaneous Ulcers In Digital Images Through Artificial Neural Networks |
Abstract | ||
|---|---|---|
Treatments of leg ulcers are generally expensive and those conducted through the direct manipulation for analysis of its evolution. The treatment efficiency is observed through the reduction of the size of ulcers in relation to the amount of tissues found in their beds, which are classified as granulated/slough. These results are obtained through analyses performed after consultation due to the time these analyses take. This work proposes a new non-invasive technique for the follow-up of treatments aimed at cutaneous ulcers. In this methodology, it was proposed that digital photos of cutaneous ulcers would be submitted to an artificial neural network (ANN), so that all surrounding the wound except for the wound itself could be extracted (skin/background), thus obtaining the ulcerated area. Computer vision techniques have been applied in order to classify the different types of tissues found in the ulcer bed, thus obtaining the corresponding granulation and slough percentages as well as its area. The results obtained have been compared with the results obtained by Image J software. Finally, this methodology will be a useful tool for health professionals in relation to the quickness and precision that it will provide results along the consultation. |
Year | Venue | Keywords |
|---|---|---|
2008 | HEALTHINF 2008: PROCEEDINGS OF THE FIRST INTERNATIONAL CONFERENCE ON HEALTH INFORMATICS, VOL 2 | leg ulcer, computer vision, artificial neural network |
Field | DocType | Citations |
Computer science,Segmentation,Digital image,Artificial intelligence,Cutaneous ulcers,Artificial neural network,Machine learning | Conference | 0 |
PageRank | References | Authors |
0.34 | 1 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| André De Souza Tarallo | 1 | 0 | 0.34 |
| Adilson Gonzaga | 2 | 80 | 13.27 |
| Marco Andrey Cipriano Frade | 3 | 5 | 1.16 |