Image processing techniques and Computer Aided Diagnosis (CAD) systems have proved to be effective for the improvement of radiologists' diagnosis. In this paper an automatic system detecting lung nodules from Postero Anterior Chest Radiographs is presented. The system extracts a set of candidate regions by applying to the radiograph three different and consecutive multi-scale schemes. The comparison of the results obtained with those presented in the literature show the efficacy of our multi-scale framework. Learning systems using as input different sets of features have been experimented for candidates classification, showing that Support Vector Machines (SVMs) can be successfully applied for this task.
|Titolo:||Lung Nodules Detection and Classification|
|Settore Scientifico Disciplinare:||Settore INF/01 - Informatica|
|Data di pubblicazione:||set-2005|
|Digital Object Identifier (DOI):||10.1109/ICIP.2005.1529951|
|Tipologia:||Book Part (author)|
|Appare nelle tipologie:||03 - Contributo in volume|