Name
Abstract | ||
|---|---|---|
Chest radiographs play an important role in the diagnosis of lung cancer. Detection of pulmonary nodules in chest radiographs form the basis of early detection. Due to its sparse bone structure and overlapping of the nodule with ribs and clavicles the nodule is hard to detect in conven- tional chest radiographs. We present a technique based on Independent Component Analysis (ICA) for the suppres- sion of posterior ribs and clavicles which will enhance the visibility of the nodule and aid the radiologist in the diagnosis process. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1109/ISSPA.2007.4555516 | information sciences, signal processing and their applications |
Keywords | Field | DocType |
blind source separation,cancer,diagnostic radiography,independent component analysis,medical image processing,tumours,blind source separation,frontal chest radiograph,independent component analysis,pulmonary nodule,rib suppression,sparse bone structure | Lung cancer,Computer vision,Lung,Rib cage,Computer science,Image segmentation,Artificial intelligence,Radiography,Independent component analysis,Radiology,Blind signal separation,Cancer | Conference |
ISBN | Citations | PageRank |
978-1-4244-1779-8 | 3 | 0.54 |
References | Authors | |
5 | 4 | |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Rasheed, T. | 1 | 3 | 0.54 |
| Bilal A. Ahmed | 2 | 61 | 17.20 |
| Khan, M.A.U. | 3 | 3 | 0.54 |
| Bettayeb, M. | 4 | 3 | 0.88 |