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Author Campadelli, Paola ♦ Casiraghi, Elena ♦ Valentini, Giorgio
Source CiteSeerX
Content type Text
File Format PDF
Language English
Subject Domain (in DDC) Computer science, information & general works ♦ Data processing & computer science
Subject Keyword Candidate Classification ♦ Image Processing Technique ♦ Postero Ante-rior Chest Radiograph ♦ Au-tomatic System ♦ Lung Nodule ♦ Support Vector Machine ♦ Candidate Region ♦ Multi-scale Framework ♦ Input Different Set ♦ Radiologist Diagnosis ♦ Lung Nodule Detection ♦ Consecutive Multi-scale Scheme
Description Image processing techniques and Computer Aided Diagno-sis (CAD) systems have proved to be effective for the im-provement of radiologists ’ diagnosis. In this paper an au-tomatic system detecting lung nodules from Postero Ante-rior 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 com-parison 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, show-ing that Support Vector Machines (SVMs) can be success-fully applied for this task. 1.
Educational Role Student ♦ Teacher
Age Range above 22 year
Educational Use Research
Education Level UG and PG ♦ Career/Technical Study
Learning Resource Type Article