The effect of different exposure parameters on radiation dose in digital mammography and digital breast tomosynthesis: A phantom study

Asbeutah, Akram M.; Brindhaban, Ajit; Almajran, Abdullah; Asbeutah, Saad A.

doi:10.1016/j.radi.2019.12.004

Cited by 3 publications

(1 citation statement)

References 25 publications

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“…In the past decade, DBT, a three-dimensional (3D) imaging technique that produces a volumetric reconstruction of the entire breast using multiple low-dose cross-sectional projections obtained by different angles of the X-ray tube, has emerged as the new gold standard for digital mammography due to its superior ability to capture previously unidentified cancers [4]. Meanwhile, DBT has higher accuracy compared to 2D imaging methods [5,6]. After acquiring several thin, highresolution images, the DBT system produces a quasi-3D format of reconstructed breast images with the aim of reducing the effect of tissue distortion.…”

Section: Introductionmentioning

confidence: 99%

Novel feature extraction based on DCT-DOST features for classification of Digital Breast Tomosynthesis images into benign and malignant tumors

Moghadam,

Rashidi

2024

Preprint

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Background: Breast cancer is caused by the uncontrolled growth of abnormal cells, resulting in a mass in the breast tissue. Early detection of the disease can significantly improve its prognosis and treatment outcome. Digital Breast Tomosynthesis, a three-dimensional imaging technology of the breast tissue, is emerging as a standard for breast imaging with improved screening and diagnostic results. The additional information obtained from tomosynthesis reduces the misleading effects of tissue overlap and improves the detection, identification, and localization of abnormalities. Benign-malignant breast tumors classification at early detection is a crucial step to improve diagnosis and prolong patient survival. The aim of this study is to classify benign-malignancy of masses in Digital Breast Tomosynthesis images based on new DCT-DOST and Radiomic features on an open database of TCIA that consist of 224 lesion bounding boxes. Methods: In order to effectively obtain both DCT-DOST and Radiomics characteristics, a 2D central slice of the DBT image, which encompasses a substantial anatomical size of the breast tumor, was employed. In the pre-processing stage, rescale intensity method was used to improve contrast and image quality. After that, by using a binary mask, the mass of the breast tissue was subjected to segmentation. Then, using radiomic and DCT-DOST features, new features were extracted from the images. In addition, we also investigated the importance of feature selection and class balancing. By pooling the radiomics and DCT-DOST features into a hybrid feature set, we investigated the compatibility of these two sets with respect to benign malignancy prediction. Results: Finally, for classification using Random Forest algorithm, K-Nearest Neighbor and Support Vector Machine, it was shown that the best result of the evaluation metrics are respectively equal to 87.80%, 78.51%, 82.78% and 75.19% in terms of mean AUC, Accuracy, Sensitivity and Specificity which was obtained by Random Forest classifier. Conclusion: The findings from the empirical analysis reveal that integrating DCT-DOST and Radiomic features into the same learning algorithm improves the discrimination power.

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Section: Introductionmentioning

confidence: 99%

Novel feature extraction based on DCT-DOST features for classification of Digital Breast Tomosynthesis images into benign and malignant tumors

Moghadam,

Rashidi

2024

Preprint

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Analysis of dual-energy mammography subtraction technique for the dose and image quality evaluation using 3D-printed breast phantom

Endarko,

Celina,

Gani

2023

Phys Eng Sci Med

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Comparison between Recorded and Measured Radiation Doses in Diagnostic Full-field Digital Mammography: A Phantom Study

Asbeutah

Brindhaban

2020

JCIS

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Objectives: There are concerns regarding the difference between directly recorded and measured entrance skin dose (ESD) and average glandular dose (AGD) in full-field digital mammography (FFDM). The objective of the study was to evaluate the effect of different exposure parameters on ESD and AGD recorded directly and measured from an FFDM unit using a phantom. Material and Methods: The ESD and AGD of 27 FFDM (craniocaudal [CC] projection) images of tissue-equivalent phantoms were acquired using a general electric (GE Senographe Essential) FFDM unit. The phantoms were used to simulate three different breast thicknesses and compositions. Tube potential, tube load, and target/ filter combinations also were recorded directly from the FFDM unit. Results: The mean differences between the directly recorded and measured ESD and AGD were 0.23 and 0.080, respectively. The 95% confidence intervals for ESD and AGD were 0.1–0.36 and 0.04–0.10, respectively. Results of paired t-test showed statistically significant difference between the directly recorded and measured ESD (P = .001) and AGD (P < .001). A positive and significant correlation was noted between the directly recorded and measured ESD (r = 0.85, P < .001) and AGD (r = 0.91, P < .001). Conclusion: This observation confirms that we can use the directly recorded doses obtained from an FFDM for quality control program.

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The effect of different exposure parameters on radiation dose in digital mammography and digital breast tomosynthesis: A phantom study

Cited by 3 publications

References 25 publications

Novel feature extraction based on DCT-DOST features for classification of Digital Breast Tomosynthesis images into benign and malignant tumors

Novel feature extraction based on DCT-DOST features for classification of Digital Breast Tomosynthesis images into benign and malignant tumors

Analysis of dual-energy mammography subtraction technique for the dose and image quality evaluation using 3D-printed breast phantom

Comparison between Recorded and Measured Radiation Doses in Diagnostic Full-field Digital Mammography: A Phantom Study

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