The recognition of breast tumor based on ultrasonic image contour features / 生物医学工程学杂志
Journal of Biomedical Engineering
;
(6): 1237-1240, 2006.
Article
in Chinese
| WPRIM
| ID: wpr-331440
ABSTRACT
The purpose of this article is to evaluate the role of quantitative margin features in the computer-aided diagnosis of malignant and benign solid breast masses using sonographic imaging. The tumour was seperated by the expert. Three contour features circurity (C), area ratio (A) and length width ratio (LWR) was caculated from the tumour contour. Then back-propagation (BP) neural network with contour features was used to classify tumors into benign and malignant. Results from 119 ultrasonic images have been applied in this experiment. BP neural network yielded the following results:
89.7% and 73.5% respectively. The methods applied in this paper are helpful to raise the correctance of breast cancer diagnosis.
Full text:
Available
Index:
WPRIM (Western Pacific)
Main subject:
Pathology
/
Image Processing, Computer-Assisted
/
Breast Neoplasms
/
Diagnostic Imaging
/
Ultrasonography
/
Neural Networks, Computer
/
Methods
Type of study:
Diagnostic study
Limits:
Female
/
Humans
Language:
Chinese
Journal:
Journal of Biomedical Engineering
Year:
2006
Type:
Article
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