A probability segmentation algorithm for lung nodules based on three-dimensional features / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 771-776, 2014.
Article
in Chinese
| WPRIM
| ID: wpr-290676
ABSTRACT
This paper presents a probability segmentation algorithm for lung nodules based on three-dimensional features. Firstly, we computed intensity and texture features in region of interest (ROI) pixel by pixel to get their feature vector, and then classified all the pixels based on their feature vector. At last, we carried region growing on the classified result, and got the final segmentation result. Using the public Lung Imaging Database Consortium (LIDC) lung nodule datasets, we verified the performance of proposed method by comparing the probability map within LIDC datasets, which was drawn by four radiology doctors separately. The experimental results showed that the segmentation algorithm using three-dimensional intensity and texture features would be effective.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Pathology
/
Algorithms
/
Probability
/
Databases, Factual
/
Imaging, Three-Dimensional
/
Lung
Type of study:
Prognostic study
Limits:
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2014
Type:
Article
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