Name
Title | ||
|---|---|---|
Classifying pulmonary nodules using dynamic enhanced CT images based on CT number histogram |
Abstract | ||
|---|---|---|
Pulmonary nodules are classified into three types such as solid, mixed GGO, and pure GGO types on the basis of the visual assessment of CT appearance. In our current study a quantitative classification algorithm has been developed by using volurnetric data sets obtained from thin-section CT images. The algorithm can classify the pulmonary nodules into five types (alpha, beta, gamma, delta, and epsilon) on the basis of internal features extracted from CT number histograms inside nodules. We applied dynamic enhanced single slice and multi slice CT images to this classification algorithm and we analyzed it in each type. |
Year | DOI | Venue |
|---|---|---|
2007 | 10.1117/12.710556 | Proceedings of SPIE |
Keywords | Field | DocType |
pulmonary nodules,CT number histogram,classification,dynamic enhanced CT images | Nuclear medicine,Histogram,Dynamic Enhanced CT,Computer-aided diagnosis,Image Series,Mathematics | Conference |
Volume | ISSN | Citations |
6514 | 0277-786X | 0 |
PageRank | References | Authors |
0.34 | 0 | 10 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Kazuhiro Minami | 1 | 92 | 9.08 |
| Yoshiki Kawata | 2 | 192 | 54.44 |
| Noboru Niki | 3 | 188 | 66.10 |
| Hironobu Ohmatsu | 4 | 138 | 45.23 |
| masahiko kusumoto | 5 | 46 | 16.28 |
| Ryutaro Kakinuma | 6 | 97 | 24.90 |
| Kenji Eguchi | 7 | 129 | 42.78 |
| Kiyoshi Mori | 8 | 47 | 10.84 |
| Masahiro Kaneko | 9 | 55 | 19.24 |
| Noriyuki Moriyama | 10 | 148 | 50.47 |