Chest X-ray features extraction for lung cancer classification

被引：0

作者：

Patil, S. A. ^{[1
]}

Udupi, V. R. ^{[1
]}

机构：

[1] Text & Engn Inst, Ichalkaranji 416115, India

来源：

JOURNAL OF SCIENTIFIC & INDUSTRIAL RESEARCH | 2010年 / 69卷 / 04期

关键词：

Active shape model (ASM); Chest X-ray; Gray level co-occurrence matrix (GLCM); Lung field segmentation; COMPUTER-AIDED DIAGNOSIS; MODEL-BASED SEGMENTATION; FEATURE-SELECTION; RADIOGRAPH SEGMENTATION; NEURAL-NETWORK; IMAGES; ALGORITHM; REGIONS; FIELDS;

D O I：

暂无

中图分类号：

T [工业技术];

学科分类号：

08 ;

摘要：

This study presents a computer algorithm, which consists of four main steps (image acquisition, image pre-processing, nodule candidate detection, and feature extraction) for nodule detection in chest radiographs. Algorithm is applied on small-cell type of lung cancer (SCLC) and non-small-cell type of lung cancer (NSCLC) images. Total 50 images (25 from each category) were used to estimate geometrical and texture features. Active shape model (ASM) was used for lung field segmentation. Gray level co-occurrence matrix (GLCM) was used to estimate texture features.

引用

页码：271 / 277

页数：7

共 32 条

[1]

[Anonymous], 2006, Digital Image Processing

[2] Automated lung segmentation in digitized posteroanterior chest radiographs [J].