Computerized characterization of contrast enhancement patterns for classifying pulmonary nodules

被引：7

作者：

Minami, K ^{[1
]}

Kawata, Y ^{[1
]}

Niki, N ^{[1
]}

Mori, K ^{[1
]}

Ohmatsu, H ^{[1
]}

Kakinuma, R ^{[1
]}

Eguchi, K ^{[1
]}

Kusumoto, M ^{[1
]}

Kaneko, M ^{[1
]}

Moriyama, N ^{[1
]}

机构：

[1] Univ Tokushima, Tokushima 7708506, Japan

来源：

MEDICAL IMAGING: 2001: IMAGE PROCESSING, PTS 1-3 | 2001年 / 4322卷

关键词：

computer-assisted diagnosis; contrast enhancement; dynamic CT; differential diagnosis; pulmonary nodules; registration; mutual information; thin-section CT images;

D O I：

10.1117/12.431087

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

This paper presents a computerized classification scheme of pulmonary nodules in contrast enhanced dynamic CT images. Conventionally, we extracted 3-D nodule images by using a deformable surface model. However, there was a limit in segmenting the 3-D nodule images contacted with vessels and bronchi. In order to improve the segmentation accuracy of the 3-D nodule images, we developed a software tool to eliminate the leaked region of the 3-D nodule image due to vessels and bronchi interactively. Using our data set including 62 cases (27 benign and 35 malignant cases), we demonstrate how the segmentation accuracy affects the, classification accuracy of our scheme.

引用

页码：1936 / 1943

页数：2

共 7 条

[1] Peripheral lung cancer: Screening and detection with low-dose spiral CT versus radiography [J].