Head and Neck Tumor Segmentation Based on Augmented Gradient Level Set Method / 生物医学工程学杂志
Journal of Biomedical Engineering
; (6): 887-904, 2015.
Article
in Zh
| WPRIM
| ID: wpr-359552
Responsible library:
WPRO
ABSTRACT
To realize the accurate positioning and quantitative volume measurement of tumor in head and neck tumor CT images, we proposed a level set method based on augmented gradient. With the introduction of gradient information in the edge indicator function, our proposed level set model is adaptive to different intensity variation, and achieves accurate tumor segmentation. The segmentation result has been used to calculate tumor volume. In large volume tumor segmentation, the proposed level set method can reduce manual intervention and enhance the segmentation accuracy. Tumor volume calculation results are close to the gold standard. From the experiment results, the augmented gradient based level set method has achieved accurate head and neck tumor segmentation. It can provide useful information to computer aided diagnosis.
Full text:
1
Index:
WPRIM
Main subject:
Pathology
/
Tomography, X-Ray Computed
/
Diagnosis, Computer-Assisted
/
Tumor Burden
/
Head and Neck Neoplasms
Type of study:
Diagnostic_studies
/
Guideline
Limits:
Humans
Language:
Zh
Journal:
Journal of Biomedical Engineering
Year:
2015
Type:
Article