RATIONALE AND OBJECTIVES: For the reconstruction of the coronary arteries from rotational angiography data, a crucial point is the selection of the optimal cardiac phase for data reconstruction. To avoid time-consuming interactive selection of the optimal cardiac phase by visual inspection of multiple high-resolution data sets reconstructed at different cardiac phases, an automatic approach for deriving optimal reconstruction windows is attractive. MATERIALS AND METHODS: This paper presents a new approach to fully automatic selection of the optimal cardiac phase for image reconstruction. It is based on the analysis of a four-dimensional data set of the region of interest reconstructed at low-spatial resolution utilizing an image quality index, which quantifies the image quality of a single three-dimensional reconstructed volume. The derived image quality index utilizes the histogram information of a single temporal snapshot as a quality measure for the vessel reconstruction. The proposed technique was applied to 16 projection data sets obtained in eight pigs. RESULTS: Experiments to evaluate the proposed method based on user-defined image quality parameters serving as ground truth, showed a relatively high correlation (>84%) for high-quality (c(phi) > 0.95) images. CONCLUSION: An image-based technique is introduced, which is able to determine the optimal cardiac phase for 3D-RCA fully automatically. The proposed method was successfully applied to 16 data sets obtained in a total of 8 porcine models.
RATIONALE AND OBJECTIVES: For the reconstruction of the coronary arteries from rotational angiography data, a crucial point is the selection of the optimal cardiac phase for data reconstruction. To avoid time-consuming interactive selection of the optimal cardiac phase by visual inspection of multiple high-resolution data sets reconstructed at different cardiac phases, an automatic approach for deriving optimal reconstruction windows is attractive. MATERIALS AND METHODS: This paper presents a new approach to fully automatic selection of the optimal cardiac phase for image reconstruction. It is based on the analysis of a four-dimensional data set of the region of interest reconstructed at low-spatial resolution utilizing an image quality index, which quantifies the image quality of a single three-dimensional reconstructed volume. The derived image quality index utilizes the histogram information of a single temporal snapshot as a quality measure for the vessel reconstruction. The proposed technique was applied to 16 projection data sets obtained in eight pigs. RESULTS: Experiments to evaluate the proposed method based on user-defined image quality parameters serving as ground truth, showed a relatively high correlation (>84%) for high-quality (c(phi) > 0.95) images. CONCLUSION: An image-based technique is introduced, which is able to determine the optimal cardiac phase for 3D-RCA fully automatically. The proposed method was successfully applied to 16 data sets obtained in a total of 8 porcine models.
Authors: Yining Hu; Lizhe Xie; Jean Claude Nunes; Jean Jacques Bellanger; Marc Bedossa; Christine Toumoulin Journal: Annu Int Conf IEEE Eng Med Biol Soc Date: 2010
Authors: Chuan Zhou; Heang-Ping Chan; Lubomir M Hadjiiski; Aamer Chughtai; Jun Wei; Ella A Kazerooni Journal: Med Phys Date: 2016-10 Impact factor: 4.071
Authors: Lubomir Hadjiiski; Jordan Liu; Heang-Ping Chan; Chuan Zhou; Jun Wei; Aamer Chughtai; Jean Kuriakose; Prachi Agarwal; Ella Kazerooni Journal: Comput Math Methods Med Date: 2016-09-19 Impact factor: 2.238