@inproceedings{8e0d0226cc1a4115816ad0b5e69eff7e,
title = "A complex dual-modality kidney phantom for renal biopsy studies",
abstract = "We developed a reliable and repeatable process to create hyper-realistic, kidney phantoms with tunable image visibility under ultrasound (US) and CT imaging modalities. A methodology was defined to create phantoms that could be produced for renal biopsy evaluation. The final complex kidney phantom was devised containing critical structures of a kidney: kidney cortex, medulla, and ureter. Simultaneously, some lesions were integrated into the phantom to mimic the presence of tumors during biopsy. The phantoms were created and scanned by ultrasound and CT scanners to verify the visibility of the complex internal structures and to observe the interactions between material properties. The result was a successful advancement in knowledge of materials with ideal acoustic and impedance properties to replicate human organs for the field of image-guided interventions.",
keywords = "Additive manufacturing, Computed tomography (CT), Image segmentation, Kidney phantom, Mold casting, Renal biopsy, Three-dimensional, Ultrtasound imaging (US)",
author = "Jose Vargas and Phuc Le and Maysam Shahedi and Jeffrey Gahan and Brett Johnson and Dormer, {James D.} and Sarah Shahub and Matthew Pfefferle and Judson, {Blake O.} and Yasmeen Alshara and Qinmei Li and Baowei Fei",
note = "Funding Information: This research was supported in part by the U.S. National Institutes of Health (NIH) grants (R01CA156775, R01CA204254, R01HL140325, and R21CA231911) and by the Cancer Prevention and Research Institute of Texas (CPRIT) grant RP190588. Publisher Copyright: {\textcopyright} 2020 SPIE.; Medical Imaging 2020: Ultrasonic Imaging and Tomography ; Conference date: 16-02-2020 Through 18-02-2020",
year = "2020",
doi = "10.1117/12.2549892",
language = "English (US)",
series = "Progress in Biomedical Optics and Imaging - Proceedings of SPIE",
publisher = "SPIE",
editor = "Byram, {Brett C.} and Ruiter, {Nicole V.}",
booktitle = "Medical Imaging 2020",
}