Breast Ultrasound Computer-Aided Diagnosis System Based on Mass Irregularity Features in Frequency Domain
| Autor: | Tahsin Nairuz, Deokwoo Lee, Jong-Ha Lee |
|---|---|
| Jazyk: | angličtina |
| Rok vydání: | 2024 |
| Předmět: |
breast cancer
computer-aided diagnosis (CAD) Breast Imaging Reporting and Data System (BI-RADS) receiver operating characteristic (ROC) tumor classification support vector machine (SVM) Technology Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 |
| Zdroj: | Applied Sciences, Vol 14, Iss 17, p 8003 (2024) |
| Druh dokumentu: | article |
| ISSN: | 2076-3417 |
| DOI: | 10.3390/app14178003 |
| Popis: | Our study develops a computer-aided diagnosis (CAD) system for breast ultrasound by presenting an innovative frequency domain technique for extracting mass irregularity features, thereby significantly boosting tumor classification accuracy. The experimental data consists of 5252 ultrasound breast tumor images, including 2745 benign tumors and 2507 malignant tumors. A Support Vector Machine was employed to classify the tumor as either benign or malignant, and the effectiveness of the proposed features set in distinguishing malignant masses from benign ones was validated. For the constructed CAD system, the performance indices’ accuracy, sensitivity, specificity, PPV, and NPV were 92.91%, 89.94%, 91.38%, 90.29%, and 91.45%, respectively, and the area index in the ROC analysis (AUC) was 0.924, demonstrating our method’s superiority over traditional spatial gray level dependence (SGLD), the ratio of depth to width, the count of depressions, and orientation features. Therefore, the constructed CAD system with the proposed features will be able to provide a precise and quick distinction between benign and malignant breast tumors with minimal training time in clinical settings. |
| Databáze: | Directory of Open Access Journals |
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