@inproceedings{64ee2c49683e4ff4982ce25ff514c7fa,
title = "Three-dimensional reconstruction and 3D printing of kidney from computed tomography",
abstract = "This paper presents a novel system to reconstruct 3D kidney structure from CT images. Before reconstruction, the kidney region should be well segmented from each CT image. This paper presents a deep learning method to segment each kidney region roughly from the CT image as initial starting points to guide a contour tracking to refine its final boundaries. However, due to the higher radiation risk from CT, a patient cannot be scanned densely so that the resolution of CT images in the Z-axis is not good enough for 3D reconstruction; that is, the distance between layers is larger than 5mm. To tackle this problem, a novel interpolation method is proposed to enhance the reconstruction results not only from the cross-section view but also the longitudinal-section view. However, the two views are not well aligned. Then, before interpolation, an alignment scheme is proposed to register the two views well. After alignment, the fine-grained 3D structure of kidney can be well reconstructed from this set of CT images with a lower-resolution in the Z axis.",
keywords = "3D printing, 3D reconstruction, CT images, Contour extraction, Vascular tissues",
author = "Huang, {Yu Zong} and Jun-Wei Hsieh and Lee, {C. H.} and Chen, {Y. C.} and Chuang, {Po Jen}",
note = "Publisher Copyright: {\textcopyright} 2018 IEEE.; 1st International Cognitive Cities Conference, IC3 2018 ; Conference date: 07-08-2018 Through 09-08-2018",
year = "2018",
month = dec,
day = "6",
doi = "10.1109/IC3.2018.00-23",
language = "English",
series = "Proceedings - 2018 1st International Cognitive Cities Conference, IC3 2018",
publisher = "Institute of Electrical and Electronics Engineers Inc.",
pages = "204--206",
booktitle = "Proceedings - 2018 1st International Cognitive Cities Conference, IC3 2018",
address = "美國",
}