Automatic Detection of Lung Cancers in Chest CT Images by the Variable N-Quoit Filter
| Autor: | T.A. Iinuma, Tomoko Miwa, Toru Matsumoto, Jun-ichi Kako, Yukio Tateno, Mitsuomi Matsumoto, Shinji Yamamoto |
|---|---|
| Rok vydání: | 2002 |
| Předmět: |
business.industry
Computer science Chest ct Filter (signal processing) Mathematical morphology Theoretical Computer Science Transformation (function) Computational Theory and Mathematics Hardware and Architecture Shadow Preprocessor Computer vision Artificial intelligence Morphological filter business Information Systems Variable (mathematics) |
| Zdroj: | Systems and Computers in Japan. 33:53-63 |
| ISSN: | 1520-684X 0882-1666 |
| DOI: | 10.1002/scj.1099 |
| Popis: | The authors have developed the quoit filter, which is a kind of mathematical morphological filter, for automatic extraction of candidate pathological areas of lung cancer. The method has problems, however, in processing speed or extraction accuracy. To overcome these problems, this paper proposes variable quoit filtering, in which the filter size is adjusted flexibly according to the pathological shadow, and distance transformation with gray-level weight is applied as preprocessing before the main filtering procedure. First, the performance of the method is analyzed using a model, and the effectiveness of the proposed method is shown. Then, trial applications to images of 82 actual cases (including 21 cancer areas) show that all of the cancer areas were correctly extracted. Compared to the conventional algorithm, the processing time is reduced to less than 1/20. © 2001 Scripta Technica, Syst Comp Jpn, 33(1): 53–63, 2002 |
| Databáze: | OpenAIRE |
| Externí odkaz: |
|
Plný text