Back to Search
Start Over
Image retrieval with principal component analysis for breast cancer diagnosis on various ultrasonic systems.
- Source :
-
Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology [Ultrasound Obstet Gynecol] 2005 Oct; Vol. 26 (5), pp. 558-66. - Publication Year :
- 2005
-
Abstract
- Objectives: We present a computer-aided diagnostic (CAD) system with textural features and image retrieval strategies for classifying benign and malignant breast tumors on various ultrasonic systems. Effective applications of CAD have used different types of texture analysis. Nevertheless, most approaches performed in a specific ultrasonic machine do not indicate whether the technique functions satisfactorily for other ultrasonic systems. This study evaluated a series of pathologically proven breast tumors using various ultrasonic systems.<br />Methods: Altogether, 600 ultrasound images of solid breast nodules comprising 230 malignant and 370 benign tumors were investigated. All ultrasound images were acquired from four diverse ultrasonic systems. The suspicious tumor area in the ultrasound image was manually chosen as the region-of-interest (ROI) subimage. Textural features extracted from the ROI subimage are supported in classifying the breast tumor as benign or malignant. However, the textural feature always behaves as a high-dimensional vector. In practice, high-dimensional vectors are unsatisfactory at differentiating breast tumors. This study applied the principal component analysis (PCA) to project the original textural features into a lower dimensional principal vector that summarized the original textural information. The image retrieval techniques were employed to differentiate breast tumors, according to the similarities of the principal vectors. The query ROI subimages were identified as malignant or benign tumors according to characteristics of retrieved images from the ultrasound image database.<br />Results: Using the proposed CAD system, historical cases could be directly added into the database without a retraining program. The area under the receiver-operating characteristics curve for the system was 0.970+/-0.006.<br />Conclusion: The CAD system identified solid breast nodules with comparatively high accuracy in the different ultrasound systems investigated.<br /> (Copyright (c) 2005 ISUOG.)
- Subjects :
- Area Under Curve
Breast Diseases classification
Breast Diseases diagnostic imaging
Breast Neoplasms classification
Databases, Factual
Female
Humans
Principal Component Analysis
Sensitivity and Specificity
Ultrasonography
Breast Neoplasms diagnostic imaging
Image Interpretation, Computer-Assisted methods
Subjects
Details
- Language :
- English
- ISSN :
- 0960-7692
- Volume :
- 26
- Issue :
- 5
- Database :
- MEDLINE
- Journal :
- Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology
- Publication Type :
- Academic Journal
- Accession number :
- 16086435
- Full Text :
- https://doi.org/10.1002/uog.1951