Mass Segmentation in Automated 3D Breast Ultrasound using Deep Learning

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Fayyaz hamed; SORYANI MOHSEN; Koozegar Ehsan; tan Tao

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Paper Information

Journal: IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING Year:2018 | Volume:12 | Issue:2 Page(s): 137-146

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Title

Mass Segmentation in Automated 3D Breast Ultrasound using Deep Learning

Author(s)

Fayyaz hamed | SORYANI MOHSEN | Koozegar Ehsan | tan Tao | Issue Writer Certificate

Keywords

Breast cancerQ1

Automated DiagnosisQ1

TumorQ1

3D ABUSQ1

Mass SegmentationQ1

Deep learningQ1

Abstract

Automated 3D breast ultrasound (ABUS) is a novel system for breast screening. It has been proposed as a supplementary modality to mammography for detection and diagnosis of Breast cancers. Although ABUS has better performance for dense breasts, reading ABUS images is time-consuming and exhausting. A computer-aided detection (CAD) system can be helpful for interpretation of ABUS images. Mass Segmentation in CADe and CADx systems play the leading role because it affects the performance of succeeding stages. Besides, it is a very challenging task because of the vast variety in size, shape, and texture of masses. Moreover, imbalanced datasets make segmentation harder. A novel Mass Segmentation approach based on Deep learning is introduced in this paper. The deep network that is used in this study for image segmentation is inspired by U-net which has been used broadly for dense segmentation in recent years. Performance was determined using a dataset of 50 masses including 38 malignant and 12 benign masses.

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APA: Copy

Fayyaz, hamed, SORYANI, MOHSEN, Koozegar, Ehsan, & tan, Tao. (2018). Mass Segmentation in Automated 3D Breast Ultrasound using Deep Learning. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, 12(2 ), 137-146. SID. https://sid.ir/paper/81625/en

Vancouver: Copy

Fayyaz hamed, SORYANI MOHSEN, Koozegar Ehsan, tan Tao. Mass Segmentation in Automated 3D Breast Ultrasound using Deep Learning. IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING[Internet]. 2018;12(2 ):137-146. Available from: https://sid.ir/paper/81625/en

IEEE: Copy

hamed Fayyaz, MOHSEN SORYANI, Ehsan Koozegar, and Tao tan, “Mass Segmentation in Automated 3D Breast Ultrasound using Deep Learning,” IRANIAN JOURNAL OF BIOMEDICAL ENGINEERING, vol. 12, no. 2 , pp. 137–146, 2018, [Online]. Available: https://sid.ir/paper/81625/en

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