Name
Abstract | ||
|---|---|---|
The present work seeks to develop a computational tool to suggest the malignancy or benignity of Solitary Lung Nodules by means of analyzing texture measures obtained from computerized tomography images.Two methods are proposed, that analyze the nodules' texture by means of the Spatial Gray Level Dependence Method and a geostatistical function denominated semivariogram. A sample with 36 nodules, 29 benign and 7 malignant, was analyzed and the preliminary results of these methods are very promising in characterizing lung nodules. The obtained results suggested that the proposed methods have great potential in the discrimination and classification of Solitary Lung Nodules. |
Year | DOI | Venue |
|---|---|---|
2005 | 10.1007/11492542_59 | IbPRIA (2) |
Keywords | Field | DocType |
lung nodule,solitary lung nodules,computerized tomography image,sgldm methods comparison,great potential,preliminary result,geostatistical function,computational tool,spatial gray level dependence,solitary lung nodule,present work | Computer vision,Variogram,Receiver operating characteristic,Lung,Pattern recognition,Computer science,Image processing,Tomography,Artificial intelligence,Gray level,Benignity | Conference |
Volume | ISSN | ISBN |
3523 | 0302-9743 | 3-540-26154-0 |
Citations | PageRank | References |
2 | 0.44 | 2 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Aristófanes C. Silva | 1 | 46 | 6.35 |
| Anselmo C. Paiva | 2 | 379 | 48.88 |
| Paulo C. P. Carvalho | 3 | 3 | 1.51 |
| Marcelo Gattass | 4 | 382 | 48.43 |