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Synthetic Bone Graft, Spinal Fusion & PET-CT

Höglund, Odd, Hedenqvist, Patricia, Rydén, Anneli   +2 more
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Synthetic CT in Musculoskeletal Disorders

Investigative Radiology, 2022
Abstract Repeated computed tomography (CT) examinations increase patients' ionizing radiation exposure and health costs, making an alternative method desirable. Cortical and trabecular bone, however, have short T2 relaxation times, causing low signal intensity on conventional magnetic resonance (MR) sequences.
Alecio F, Lombardi, Ya-Jun, Ma, Hyungseok, Jang, Saeed, Jerban, Jiang, Du, Eric Y, Chang, Christine B, Chung   +6 more
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Synthetic dual-energy CT reconstruction from single-energy CT Using artificial intelligence

Abdominal Radiology, 2023
To develop and assess the utility of synthetic dual-energy CT (sDECT) images generated from single-energy CT (SECT) using two state-of-the-art generative adversarial network (GAN) architectures for artificial intelligence-based image translation.In this retrospective study, 734 patients (389F; 62.8 years ± 14.9) who underwent enhanced DECT of the chest,
Jiwoong Jeong, Andrew Wentland, Domenico Mastrodicasa, Ghaneh Fananapazir, Adam Wang, Imon Banerjee, Bhavik N. Patel   +6 more
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Synthetic CT generation from CBCT using double-chain-CycleGAN

Computers in Biology and Medicine, 2023
Cone-beam CT (CBCT) has the advantage of being less expensive, lower radiation dose, less harm to patients, and higher spatial resolution. However, noticeable noise and defects, such as bone and metal artifacts, limit its clinical application in adaptive radiotherapy.
Liwei, Deng, Yufei, Ji, Sijuan, Huang, Xin, Yang, Jing, Wang   +4 more
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Synthetic CT generation based on CBCT using respath‐cycleGAN

Medical Physics, 2022
AbstractPurposeCone‐beam computed tomography (CBCT) plays an important role in radiotherapy, but the presence of a large number of artifacts limits its application. The purpose of this study was to use respath‐cycleGAN to synthesize CT (sCT) similar to planning CT (pCT) from CBCT for future clinical practice.MethodsThe method integrates the respath ...
Liwei, Deng, Jie, Hu, Jing, Wang, Sijuan, Huang, Xin, Yang   +4 more
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UTE‐mDixon‐based thorax synthetic CT generation

Medical Physics, 2019
PurposeAccurate photon attenuation assessment from MR data remains an unmet challenge in the thorax due to tissue heterogeneity and the difficulty of MR lung imaging. As thoracic tissues encompass the whole physiologic range of photon absorption, large errors can occur when using, for example, a uniform, water‐equivalent or a soft‐tissue‐only ...
Kuan-Hao, Su, Harry T, Friel, Jung-Wen, Kuo, Rose, Al Helo, Atallah, Baydoun, Christian, Stehning, Adina N, Crisan, Melanie S, Traughber, Ajit, Devaraj, David W, Jordan, Pengjiang, Qian, Asha, Leisser, Rodney J, Ellis, Karin A, Herrmann, Norbert, Avril, Bryan J, Traughber, Raymond F, Muzic   +16 more
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Synthetic CT-aided MRI-CT image registration for head and neck radiotherapy

Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020
In this study, we propose a synthetic CT (sCT) aided MRI-CT deformable image registration for head and neck radiotherapy. An image synthesis network, cycle consistent generative adversarial network (CycleGAN), was first trained using 25 pre-aligned CT-MRI image pairs.
Yabo Fu, Yang Lei, Jun Zhou, Tonghe Wang, David S. Yu, Jonathan J. Beitler, Walter J. Curran, Tian Liu, Xiaofeng Yang   +8 more
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Multi-organ segmentation in pelvic CT images with CT-based synthetic MRI

Medical Imaging 2020: Biomedical Applications in Molecular, Structural, and Functional Imaging, 2020
We propose a hybrid deep learning-based method, which includes a cycle consistent generative adversarial network (CycleGAN) and deep attention fully convolution network implemented by a U-Net (DAUnet), to perform volumetric multi-organ segmentation for pelvic computed tomography (CT).
Yang Lei, Xue Dong, Sibo Tian, Tonghe Wang, Pretesh Patel, Walter J. Curran, Ashesh B. Jani, Tian Liu, Xiaofeng Yang   +8 more
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Synthetic CT generation from CBCT images via unsupervised deep learning

Physics in Medicine & Biology, 2021
Abstract Adaptive-radiation-therapy (ART) is applied to account for anatomical variations observed over the treatment course. Daily or weekly cone-beam computed tomography (CBCT) is commonly used in clinic for patient positioning, but CBCT’s inaccuracy in Hounsfield units (HU) prevents its application to dose calculation and treatment
Liyuan Chen, Xiao Liang, Chenyang Shen, Dan Nguyen, Steve Jiang, Jing Wang   +5 more
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