QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION
Abstract & Details
Research Area
Computer Engineering
Keywords
deep learning
machine learning
breast cancer detection
Abstract
Breast cancer is one of the most diagnosed types of cancer worldwide. Volumetric ultrasound breast imaging, combined with MRI can improve lesion detection rate, reduce examination time, and improve lesion diagnosis. However, to our knowledge, there are no 3D US breast imaging systems available that facilitate 3D US – MRI image fusion. In this paper, a novel Automated Cone-based Breast Ultrasound System (ACBUS) is introduced. The system facilitates volumetric ultrasound acquisition of the breast in a prone position without deforming it by the US transducer. Quality of ACBUS images for reconstructions at different voxel sizes (0.25 and 0.50 mm isotropic) was compared to quality of the Automated Breast Volumetric Scanner (ABVS) (Siemens Ultrasound, Issaquah, WA, USA) in terms of signal-to-noise ratio (SNR), contrast-to-noise ratio (CNR), and resolution using a custom made phantom. The ACBUS image data were registered to MRI image data utilizing surface matching and the registration accuracy was quantified using an internal marker. The technology was also evaluated in vivo. The phantom-based quantitative analysis demonstrated that ACBUS can deliver volumetric breast images with an image quality similar to the images delivered by a currently commercially available Siemens ABVS. We demonstrate on the phantom and in vivo that ACBUS enables adequate MRI-3D US fusion. To our conclusion, ACBUS might be a suitable candidate for a second-look breast US exam, patient follow-up, and US guided biopsy planning.
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Author Information
| # | Name | Institute / Affiliation |
|---|---|---|
| 1 | Lidhi P | IES College of Engineering |
How to Cite
Use the following formats to cite this article in your research.
APA Style
P, Lidhi (2022). QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION. International Journal of Advance Research and Innovative Ideas In Education, 8(3), 5231-5235.
MLA Style
P, Lidhi. "QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION." International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, 2022, pp. 5231-5235.
IEEE Style
Lidhi P, "QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION," International Journal of Advance Research and Innovative Ideas In Education, vol. 8, no. 3, pp. 5231-5235, 2022.
Vancouver Style
P Lidhi. QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION. International Journal of Advance Research and Innovative Ideas In Education. 2022;8(3):5231-5235.
Harvard Style
P, Lidhi (2022) 'QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION', International Journal of Advance Research and Innovative Ideas In Education, 8(3), pp. 5231-5235.
Chicago Style
P, Lidhi. "QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 5231-5235.
Turabian Style
P, Lidhi. "QUANTITATIVE EVALUATION OF AN AUTOMATED CONE-BASED BREAST ULTRASOUND SCANNER FOR MRI 3D US IMAGE FUSION." International Journal of Advance Research and Innovative Ideas In Education 8, no. 3 (2022): 5231-5235.
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