Abstract
Radiologists likely incorrectly classify benign masses as Breast Imaging Reporting and Data System (BIRADS) category 3. A computer-aided diagnosis (CAD) system was developed in this study as a second viewer to avoid misclassification of carcinomas. Sixty-nine biopsy-proven BI-RADS category 3 masses, including 21 malignant and 48 benign masses, were used to evaluate the CAD system. To improve the texture features, gray-scale variations between images were reduced by transforming pixels into intensity-invariant ranklet coefficients. The textures of the tumor and speckle pixels were extracted from the transformed ranklet images to provide more robust features than in conventionalCADsystems. As a result, tumor texture and speckle texture with ranklet transformation achieved significantly better areas under the receiver operating characteristic curve (Az) compared with those without ranklet transformation (Az = 0.83 vs. 0.58 and Az = 0.80 vs. 0.56, p value <0.05). The improved CAD system can be a second reader to confirm the classification of BI-RADS category 3 masses.
| Original language | English |
|---|---|
| Pages (from-to) | 2039-2048 |
| Number of pages | 10 |
| Journal | Ultrasound in Medicine and Biology |
| Volume | 41 |
| Issue number | 7 |
| DOIs | |
| Publication status | Published - 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
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SDG 3 Good Health and Well-being
Keywords
- Breast cancer
- Breast imaging and reporting data system
- Computer-aided diagnosis
- Ranklet
- Ultrasound
ASJC Scopus subject areas
- Biophysics
- Radiological and Ultrasound Technology
- Acoustics and Ultrasonics
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