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Updated: Mar 15, 2026
Integrating Augmented Reality Tools in Breast Cancer Related Lymphedema Prognostication and Diagnosis
Published on: February 6, 2020
Segmentation and three-dimensional reconstruction of lesions using the automated breast volume scanner (ABVS)
Teresa Araújo1,2, Momen Abayazid1,3, Matthieu J C M Rutten4
1Department of Biomechanical Engineering, University of Twente, P. O. Box 217, 7500 AE, Enschede, Overijsel, Netherlands.
Background:
Ultrasound is an effective tool for breast cancer diagnosis. However, its relatively low image quality makes small lesion analysis challenging. This promotes the development of tools to help clinicians in the diagnosis.
Methods:
We propose a method for segmentation and three-dimensional (3D) reconstruction of lesions from ultrasound images acquired using the automated breast volume scanner (ABVS). Segmentation and reconstruction algorithms are applied to obtain the lesion's 3D geometry. A total of 140 artificial lesions with different sizes and shapes are reconstructed in gelatin-based phantoms and biological tissue. Dice similarity coefficient (DSC) is used to evaluate the reconstructed shapes. The algorithm is tested using a human breast phantom and clinical data from six patients.
Results:
DSC values are 0.86 ± 0.06 and 0.86 ± 0.05 for gelatin-based phantoms and biological tissue, respectively. The results are validated by a specialized clinician.
Conclusions:
Evaluation metrics show that the algorithm accurately segments and reconstructs various lesions. Copyright © 2016 John Wiley & Sons, Ltd.
