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A list of all the posts and pages found on the site. For you robots out there is an XML version available for digesting as well.
Pages
About me
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Posts
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Blog Post number 4
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Blog Post number 1
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portfolio
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publications
SPECT/CT scatter estimation using a deep convolutional neural network: implementation in Y-90 imaging
Published in 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC)., 2019
Recommended citation: Xiang, Haowei, et al. "SPECT/CT scatter estimation using a deep convolutional neural network: implementation in Y-90 imaging." 2019 IEEE Nuclear Science Symposium and Medical Imaging Conference (NSS/MIC). IEEE, 2019. https://ieeexplore.ieee.org/document/9060019
A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions
Published in European journal of nuclear medicine and molecular imaging, 2020
Recommended citation: Xiang, Haowei, et al. "A deep neural network for fast and accurate scatter estimation in quantitative SPECT/CT under challenging scatter conditions." European journal of nuclear medicine and molecular imaging 47 (2020): 2956-2967. https://link.springer.com/article/10.1007/s00259-020-04840-9
Model-based Image Reconstruction in Looping-star MRI
Published in ISMRM, 2022
Recommended citation: Xiang, Haowei, Jeffrey A. Fessler, and Douglas C. Noll. "Model-based Image Reconstruction in Looping-star MRI." 2022 ISMRM https://archive.ismrm.org/2022/2346.html
Accelerated convolutional operator learning
Published in Preprint, 20109
Recommended citation: Xiyu Zhang, Haowei Xiang, Il Yong Chun, Mert Pilanci, and Jeffrey A. Fessler, Preprint
talks
teaching
Graduate Student Instructor: Matrix Methods for Signal Processing, Data Analysis and Machine Learning
Graduate course EECS 551: Matrix Methods for Signal Processing, Data Analysis and Machine Learning, University of Michigan, Electrical Engineering and Computer Science, 2020
Graduate Student Instructor: Probability and Random Process
Graduate course EECS 501: Probability and Random Process, University of Michigan, Electrical Engineering and Computer Science, 2023