Segmentation and three-dimensional reconstruction of lesions using the automated breast volume scanner (ABVS)

Teresa Araújo, Momen Abayazid*, Matthieu J.C.M. Rutten, Sarthak Misra

*Corresponding author for this work

    Research output: Contribution to journalArticleAcademicpeer-review

    10 Citations (Scopus)
    13 Downloads (Pure)

    Abstract

    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
    Original languageEnglish
    Article numbere1767
    JournalInternational journal of medical robotics and computer assisted surgery
    Volume13
    Issue number3
    DOIs
    Publication statusPublished - Sept 2017

    Keywords

    • 2023 OA procedure

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