Lightweight mesh detection and analysis in automated breast ultrasound using deep convolutional neural networks and level set method

Wei Bai; Jun Wu; Liang Sun; Rong Wang; Juan Tian

doi:10.1117/12.2628676

7 March 2022 Lightweight mesh detection and analysis in automated breast ultrasound using deep convolutional neural networks and level set method

Wei Bai, Jun Wu, Liang Sun, Rong Wang, Juan Tian

Author Affiliations +

Proceedings Volume 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021); 121671I (2022) https://doi.org/10.1117/12.2628676
Event: 2021 Third International Conference on Electronics and Communication, Network and Computer Technology, 2021, Harbin, China

Abstract

In abdominal hernia surgery, accurate detection of the Lightweight (LW) mesh has critical clinical significance for the diagnosis and treatment of mesh-related complications. Reviewing the large number of slices produced by Automated Breast Ultrasound (ABUS), however, is not only time-consuming and laborious but also easy to miss or misdiagnose the micro-structured LW mesh near the fascia tissue. Therefore, in this paper, an automatic and accurate computer-aided detection system based on deep convolutional neural networks and the level set method is proposed to improve this review. Firstly, the ABUS image is pre-processed using an intelligent speckle reducing anisotropic diffusion (ISRAD) to enhance the edge details of the LW mesh while reducing speckle noise. Then, combine the ROI prior information output by the deep convolutional neural networks and the level set method to outline the contour of the LW mesh. Finally, 3D reconstruction, and analysis of the LW mesh changes over time. The LW mesh with different imaging time, sizes, degrees of aggregation (DOA), and imaging depths are used to test the proposed method, experimental results show that the proposed method has a satisfactory application for detecting and analyzing the LW mesh in ABUS images.

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Wei Bai, Jun Wu, Liang Sun, Rong Wang, and Juan Tian "Lightweight mesh detection and analysis in automated breast ultrasound using deep convolutional neural networks and level set method", Proc. SPIE 12167, Third International Conference on Electronics and Communication; Network and Computer Technology (ECNCT 2021), 121671I (7 March 2022); https://doi.org/10.1117/12.2628676

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KEYWORDS

Convolutional neural networks

Speckle

3D modeling

Computer aided diagnosis and therapy

Denoising

Ultrasonography

Breast

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