Name
Title | ||
|---|---|---|
Computer-aided diagnosis system for lung nodules based on computed tomography using shape analysis, a genetic algorithm, and SVM. |
Abstract | ||
|---|---|---|
Lung cancer is the major cause of death among patients with cancer worldwide. This work is intended to develop a methodology for the diagnosis of lung nodules using images from the Image Database Consortium and Image Database Resource Initiative (LIDC-IDRI). The proposed methodology uses image processing and pattern recognition techniques. To differentiate the patterns of malignant and benign forms, we used a Minkowski functional, distance measures, representation of the vector of points measures, triangulation measures, and Feret diameters. Finally, we applied a genetic algorithm to select the best model and a support vector machine for classification. In the test stage, we applied the proposed methodology to 1405 (394 malignant and 1011 benign) nodules from the LIDC-IDRI database. The proposed methodology shows promising results for diagnosis of malignant and benign forms, achieving accuracy of 93.19 %, sensitivity of 92.75 %, and specificity of 93.33 %. The results are promising and demonstrate a good rate of correct detections using the shape features. Because early detection allows faster therapeutic intervention, and thus a more favorable prognosis for the patient, herein we propose a methodology that contributes to the area. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1007/s11517-016-1577-7 | Med. Biol. Engineering and Computing |
Keywords | Field | DocType |
Genetic algorithm,Lung cancer,Medical image,Shape analysis | Lung cancer,Computer vision,Computer-aided diagnosis,Support vector machine,Image processing,Triangulation (social science),Artificial intelligence,Mathematics,Genetic algorithm,Distance measures,Shape analysis (digital geometry) | Journal |
Volume | Issue | ISSN |
55 | 8 | 1741-0444 |
Citations | PageRank | References |
0 | 0.34 | 5 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Antonio Oseas de Carvalho Filho | 1 | 75 | 6.57 |
| Aristófanes Corrêa Silva | 2 | 4 | 0.95 |
| Anselmo C. Paiva | 3 | 379 | 48.88 |
| Rodolfo Acatauassú Nunes | 4 | 0 | 0.34 |
| Marcelo Gattass | 5 | 382 | 48.43 |