Improving deformable image registration with point metric and masking technique for postoperative breast cancer radiotherapy | Zendy

Xin Xie | Zendy; Yuchun Song | Zendy; Feng Ye | Zendy; Hui Yan | Zendy; Shulian Wang | Zendy; Xinming Zhao | Zendy; Jianrong Dai | Zendy

Open Access

Improving deformable image registration with point metric and masking technique for postoperative breast cancer radiotherapy

Author(s) -

Xin Xie,

Yuchun Song,

Feng Ye,

Hui Yan,

Shulian Wang,

Xinming Zhao,

Jianrong Dai

Publication year - 2021

Publication title -

quantitative imaging in medicine and surgery

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.766

H-Index - 21

eISSN - 2223-4292

pISSN - 2223-4306

DOI - 10.21037/qims-20-705

Subject(s) - masking (illustration) , metric (unit) , image registration , breast cancer , computer science , radiation therapy , artificial intelligence , point (geometry) , computer vision , medicine , medical physics , radiology , cancer , image (mathematics) , mathematics , art , operations management , economics , visual arts , geometry

Deformable image registration (DIR) is increasingly used for target volume definition in radiotherapy. However, this method is challenging for postoperative breast cancer patients due to the large deformations and non-correspondence caused by tumor resection and clip insertion. In this study, an improved B-splines based DIR method was developed to address this issue for higher registration accuracy.

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