ArticleSensors (Basel, Switzerland)2017
Efficient Segmentation of a Breast in B-Mode Ultrasound Tomography Using Three-Dimensional GrabCut (GC3D).
Article in Sensors (Basel, Switzerland), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
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Who cites it
8 citing papers in PubMed, 24 citations in OpenAlex.
- Benchmarking YOLOs in breast ultrasound lesion segmentation.Quantitative imaging in medicine and surgery · 2026Article
- Estimation of drinking water volume of laboratory animals based on image processing.Scientific reports · 2023Article
- Accurate breast cancer diagnosis using a stable feature ranking algorithm.BMC medical informatics and decision making · 2023Article
- To Align Multimodal Lumbar Spine Images via Bending Energy Constrained Normalized Mutual Information.BioMed research international · 2020Article
- One View Per City for Buildings Segmentation in Remote-Sensing Images via Fully Convolutional Networks: A Proof-of-Concept Study.Sensors (Basel, Switzerland) · 2019Article
- A Technical Review of Convolutional Neural Network-Based Mammographic Breast Cancer Diagnosis.Computational and mathematical methods in medicine · 2019Review
- A consistency evaluation of signal-to-noise ratio in the quality assessment of human brain magnetic resonance images.BMC medical imaging · 2018Article
- The Application of an Ultrasound Tomography Algorithm in a Novel Ring 3D Ultrasound Imaging System.Sensors (Basel, Switzerland) · 2018Article
Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As an emerging modality for whole breast imaging, ultrasound tomography (UST), has been adopted for diagnostic purposes. Efficient segmentation of an entire breast in UST images plays an important role in quantitative tissue analysis and cancer diagnosis, while major existing methods suffer from considerable time consumption and intensive user interaction. This paper explores three-dimensional GrabCut (GC3D) for breast isolation in thirty reflection (B-mode) UST volumetric images. The algorithm can be conveniently initialized by localizing points to form a polygon, which covers the potential breast region. Moreover, two other variations of GrabCut and an active contour method were compared. Algorithm performance was evaluated from volume overlap ratios ( T O , target overlap; M O , mean overlap; F P , false positive; F N , false negative) and time consumption. Experimental results indicate that GC3D considerably reduced the work load and achieved good performance ( T O = 0.84; M O = 0.91; F P = 0.006; F N = 0.16) within an average of 1.2 min per volume. Furthermore, GC3D is not only user friendly, but also robust to various inputs, suggesting its great potential to facilitate clinical applications during whole-breast UST imaging. In the near future, the implemented GC3D can be easily automated to tackle B-mode UST volumetric images acquired from the updated imaging system.
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