Surface-based volumetric image reconstruction for image-guided procedures using a data-driven framework Conference Paper


Authors: Chang, C. W.; Pan, S.; Tian, Z.; Wang, T.; Axente, M.; Shelton, J.; Liu, T.; Roper, J.; Yang, X.
Title: Surface-based volumetric image reconstruction for image-guided procedures using a data-driven framework
Conference Title: SPIE Medical Imaging 2024: Image-Guided Procedures, Robotic Interventions, and Modeling
Abstract: The advent of computed tomography significantly improves patients' health regarding diagnosis, prognosis, and treatment planning and image-guided radiotherapy. However, tomographic imaging cannot achieve real-Time imaging and the imaging escalates concomitant radiation doses to patients, inducing potential secondary cancer by 4%. We demonstrate the feasibility of a data-driven approach to synthesize volumetric images using patients' surface images, which can be obtained from a zero-dose surface imaging system. This study includes 500 computed tomography (CT) image sets from 50 patients. Compared to the ground truth CT, the synthetic images result in the evaluation metric values of 26.9 ± 4.1 Hounsfield units, 39.1 ± 1.0 dB, and 0.97 ± 0.01 regarding the mean absolute error, peak signal-To-noise ratio, and structural similarity index measure. This approach provides a data integration solution that can potentially enable real-Time imaging, which is free of radiation-induced risk and could be applied to image-guided medical procedures. © COPYRIGHT SPIE. Downloading of the abstract is permitted for personal use only.
Keywords: treatment planning; radiotherapy; image enhancement; computerized tomography; medical imaging; diagnosis; image reconstruction; image guided radiotherapy; signal to noise ratio; image-guided procedures; data integration; surface-based; data driven; images reconstruction; patient health; volumetric images; diagnosis planning; realtime imaging
Journal Title Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Volume: 12928
Conference Dates: 2024 Feb 19-22
Conference Location: San Deigo, CA
ISBN: 1605-7422
Publisher: SPIE  
Date Published: 2024-01-01
Start Page: 1292822
Language: English
DOI: 10.1117/12.3006510
PROVIDER: scopus
DOI/URL:
Notes: Conference paper -- Source: Scopus
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  1. Tonghe Wang
    51 Wang