Name
Abstract | ||
|---|---|---|
This paper proposes methods for automated extraction of emphysematous lesions from three-dimensional (3-D) CT images and quantitative evaluation of their distribution pattern. We employ 3-D image processing techniques on computer-aided diagnosis of pulmonary emphysema. Emphysematous lesions are automatically extracted by a region growing method. To analyze spatial distribution of the detected low-attenuation areas, we examine the relations between emphysematous lesions and bronchi or pulmonary blood vessels using Euclidean distance transformation. Experimental results show that the methods could be used to extract emphysematous lesions appropriately and could quantitatively evaluate their distribution pattern. |
Year | DOI | Venue |
|---|---|---|
2003 | 10.1007/978-3-540-39899-8_89 | LECTURE NOTES IN COMPUTER SCIENCE |
Keywords | Field | DocType |
region growing,three dimensional,euclidean distance | COPD,Computer vision,Pattern recognition,Computer science,Pulmonary blood vessel,Euclidean distance,Image processing,Artificial intelligence,Region growing,Cad system | Conference |
Volume | ISSN | Citations |
2878 | 0302-9743 | 4 |
PageRank | References | Authors |
0.53 | 1 | 7 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Jiro Nagao | 1 | 18 | 2.04 |
| Takahisa Aiguchi | 2 | 4 | 0.87 |
| Kensaku Mori | 3 | 1125 | 160.28 |
| Y Suenaga | 4 | 737 | 187.41 |
| Jun-ichiro Toriwaki | 5 | 578 | 136.04 |
| Masaki Mori | 6 | 144 | 17.48 |
| Hiroshi Natori | 7 | 220 | 28.49 |