Hideharu Miura1, Shuichi Ozawa2, Minoru Nakao3, Kengo Furukawa3, Yoshiko Doi3, Hideo Kawabata3, Masahiro Kenjou3, Yasushi Nagata2. 1. Hiroshima High-Precision Radiotherapy Cancer Center, 3-2-2, Futabanosato, Higashi-ku, Hiroshima 732-0057, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, 1-2-3, Kasumi, Minami-ku, Hiroshima 734-8551, Japan. Electronic address: miura@hiprac.jp. 2. Hiroshima High-Precision Radiotherapy Cancer Center, 3-2-2, Futabanosato, Higashi-ku, Hiroshima 732-0057, Japan; Department of Radiation Oncology, Institute of Biomedical & Health Science, Hiroshima University, 1-2-3, Kasumi, Minami-ku, Hiroshima 734-8551, Japan. 3. Hiroshima High-Precision Radiotherapy Cancer Center, 3-2-2, Futabanosato, Higashi-ku, Hiroshima 732-0057, Japan.
Abstract
PURPOSE: We assessed the deformable image registration (DIR) accuracy of thoracic images under different regularization weights using commercially available DIR software. METHODS: The thoracic 4-dimensional (4D) CT images of 10 patients were used. The datasets for these patients were provided by DIR-lab (www.dir-lab.com) and included a coordinate list of 300 anatomic landmarks that had been manually identified. The ANAtomically CONstrained Deformation Algorithm (ANACONDA) of RayStation (RaySearch Laboratories, Stockholm, Sweden) was used to deform the peak-inhale to peak-exhale images under different regularization weights (4, 40, 400-default setting, 1500, 4000, 10,000, 15,000, 20,000, 30,000, and 40,000). The regularization weights were changed using a script. The registration error (RE) was determined by calculating the difference at each landmark point between the displacement calculated by the DIR software and that calculated by the landmark. We measured the computation time for each regularization weight setting. RESULTS: High regularization weights resulted in a smaller RE than that observed with lower regularization weights. The RE decreases rapidly with increase in regularization weight before reaching a plateau. No significant difference was found between a regularization weight of 400 and regularization weights of 4, 40, 4000 or 40,000 (P value >0.05). The range of the average time was 8.4-12.2s. CONCLUSIONS: We concluded that the default setting for ANACONDA is stable with respect to regularization weight in the thoracic region.
PURPOSE: We assessed the deformable image registration (DIR) accuracy of thoracic images under different regularization weights using commercially available DIR software. METHODS: The thoracic 4-dimensional (4D) CT images of 10 patients were used. The datasets for these patients were provided by DIR-lab (www.dir-lab.com) and included a coordinate list of 300 anatomic landmarks that had been manually identified. The ANAtomically CONstrained Deformation Algorithm (ANACONDA) of RayStation (RaySearch Laboratories, Stockholm, Sweden) was used to deform the peak-inhale to peak-exhale images under different regularization weights (4, 40, 400-default setting, 1500, 4000, 10,000, 15,000, 20,000, 30,000, and 40,000). The regularization weights were changed using a script. The registration error (RE) was determined by calculating the difference at each landmark point between the displacement calculated by the DIR software and that calculated by the landmark. We measured the computation time for each regularization weight setting. RESULTS: High regularization weights resulted in a smaller RE than that observed with lower regularization weights. The RE decreases rapidly with increase in regularization weight before reaching a plateau. No significant difference was found between a regularization weight of 400 and regularization weights of 4, 40, 4000 or 40,000 (P value >0.05). The range of the average time was 8.4-12.2s. CONCLUSIONS: We concluded that the default setting for ANACONDA is stable with respect to regularization weight in the thoracic region.
Authors: Yuncheng Zhong; Yevgeniy Vinogradskiy; Liyuan Chen; Nick Myziuk; Richard Castillo; Edward Castillo; Thomas Guerrero; Steve Jiang; Jing Wang Journal: Med Phys Date: 2019-03-12 Impact factor: 4.071
Authors: Philipp Hoegen; Clemens Lang; Sati Akbaba; Peter Häring; Mona Splinter; Annette Miltner; Marion Bachmann; Christiane Stahl-Arnsberger; Thomas Brechter; Rami A El Shafie; Fabian Weykamp; Laila König; Jürgen Debus; Juliane Hörner-Rieber Journal: Front Oncol Date: 2020-12-09 Impact factor: 6.244