Towards generating personalized volumetric phantom from patient’s surface geometry

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Abstract

This paper presents a method to generate a volumetric phantom with internal anatomical structures from the patient’s skin surface geometry, and studies the potential impact of this technology on planning medical scans and procedures such as patient positioning. Existing scan planning for imaging is either done by visual inspection of the patient or based on an ionizing scan obtained prior to the full scan. These methods are either limited in accuracy or result in additional radiation dose to the patient. Our approach generates a “CT”-like phantom, with lungs and bone structures, from the patient’s skin surface. The skin surface can be estimated from a 2.5D depth sensor and thus, the proposed method offers a novel solution to reduce the radiation dose. We present quantitative experiments on a dataset of 2045 whole body CT scans and report measurements relevant to the potential clinical use of such phantoms. (This feature is based on research, and is not commercially available. Due to regulatory reasons its future availability cannot be guaranteed.)

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APA

Wu, Y., Singh, V., Teixeira, B., Ma, K., Tamersoy, B., Krauss, A., & Chen, T. (2018). Towards generating personalized volumetric phantom from patient’s surface geometry. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 11070 LNCS, pp. 171–179). Springer Verlag. https://doi.org/10.1007/978-3-030-00928-1_20

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