Zobrazeno 1 - 10
of 1 317
pro vyhledávání: '"Pan Xiaochuan"'
Autor:
Phillips, JP, Sidky, Emil Y., Terzioglu, Fatma, Reiser, Ingrid S., Bal, Guillaume, Pan, Xiaochuan
The goal of this work is to study occurrences of non-unique solutions in dual-energy CT (DECT) for objects containing water and a contrast agent. Previous studies of the Jacobian of nonlinear systems identified that a vanishing Jacobian determinant i
Externí odkaz:
http://arxiv.org/abs/2411.12862
Autor:
Sidky, Emil Y., Wu, Xiangyi, Duan, Xiaoyu, Huang, Hailing, Zhao, Wei, Zhang, Leo Y., Phillips, John Paul, Zhang, Zheng, Chen, Buxin, Xia, Dan, Reiser, Ingrid S., Pan, Xiaochuan
An optimization-based image reconstruction algorithm is developed for contrast enhanced digital breast tomosynthesis (DBT) using dual-energy scanning. The algorithm minimizes directional total variation (TV) with a data discrepancy and non-negativity
Externí odkaz:
http://arxiv.org/abs/2406.07306
Deep neural networks used for reconstructing sparse-view CT data are typically trained by minimizing a pixel-wise mean-squared error or similar loss function over a set of training images. However, networks trained with such pixel-wise losses are pro
Externí odkaz:
http://arxiv.org/abs/2402.10010
Autor:
Terzioglu, Fatma, Sidky, Emil Y., Phillips, Jp, Reiser, Ingrid, Bal, Guillaume, Pan, Xiaochuan
Purpose: This study proposes a systematic method for determining the optimal x-ray tube settings/energy windows and fluence for minimal noise and maximum CNR in material density images obtained from DECT scans by fixing the subject size and the total
Externí odkaz:
http://arxiv.org/abs/2308.00212
Publikováno v:
Journal of Mathematical Imaging and Vision 2024
This work investigates conditions for quantitative image reconstruction in multispectral computed tomography (MSCT), which remains a topic of active research. In MSCT, one seeks to obtain from data the spatial distribution of linear attenuation coeff
Externí odkaz:
http://arxiv.org/abs/2305.03330
Autor:
Zhang, Zheng, Epel, Boris, Chen, Buxin, Xia, Dan, Sidky, Emil Y., Qiao, Zhiwei, Halpern, Howard, Pan, Xiaochuan
Objective: We investigate and develop optimization-based algorithms for accurate reconstruction of four-dimensional (4D)-spectral-spatial (SS) images directly from data collected over limited angular ranges (LARs) in continuous-wave (CW) electron par
Externí odkaz:
http://arxiv.org/abs/2304.00209
An alternating direction method of multipliers (ADMM) framework is developed for nonsmooth biconvex optimization for inverse problems in imaging. In particular, the simultaneous estimation of activity and attenuation (SAA) problem in time-of-flight p
Externí odkaz:
http://arxiv.org/abs/2303.17042
Autor:
Pan, Xiaochuan, Sidky, Emil Y.
Quantitative image reconstruction in dual-energy computed tomography (CT) remains a topic of active research. We read with interest ``DIRECT-Net: A unified mutual-domain material decomposition network for quantitative dual-energy CT imaging,'' which
Externí odkaz:
http://arxiv.org/abs/2212.08953
Autor:
Sidky, Emil Y., Pan, Xiaochuan
This Special Report summarizes the 2022 AAPM Grand Challenge on Deep-Learning spectral Computed Tomography (DL-spectral CT) image reconstruction. The purpose of the challenge is to develop the most accurate image reconstruction algorithm for solving
Externí odkaz:
http://arxiv.org/abs/2212.06718
The generalized minimal residual (GMRES) algorithm is applied to image reconstruction using linear computed tomography (CT) models. The GMRES algorithm iteratively solves square, non-symmetric linear systems and it has practical application to CT whe
Externí odkaz:
http://arxiv.org/abs/2201.07408