| Title | A multiclassifier approach for lung nodule classification |
| Publication Type | Book |
| Year of Publication | 2006 |
| Authors | Pereira, CS, Alexandre, LA, Mendonça, AM, Campilho, A |
| Series Title | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)Lect. Notes Comput. Sci. |
| Volume | 4142 LNCS |
| Number of Pages | 612 - 623 |
| City | Povoa de Varzim |
| ISBN Number | 03029743 (ISSN); 3540448942 (ISBN); 9783540448945 (ISBN) |
| Keywords | Biological organs, Classification (of information), Computer aided diagnosis, False-positives nodules, Medical imaging, Multi-orientation filter bank, Radiography, X rays, X-ray chest radiographs |
| Abstract | The aim of this paper is to examine a multiclassifier approach to the classification of the lung nodules in X-ray chest radiographs. The approach investigated here is based on an image region-based classification whose output is the information of the presence or absence of a nodule in an image region. The classification was made, essentially, in two steps: firstly, a set of rotation invariant features was extracted from the responses of a multi-scale and multi-orientation filter bank; secondly, different classifiers (multi-layer perceptrons) are designed using different features sets and trained in different data. These classifiers are further combined in order to improve the classification performance. The obtained results are promising and can be used for reducing the false-positives nodules detected in a computer-aided diagnosis system. © Springer-Verlag Berlin Heidelberg 2006. |
| URL | http://www.scopus.com/inward/record.url?eid=2-s2.0-33749658606&partnerID=40&md5=f6e83e868f5b1ee08b400ee9191138cd |
