Full Text Journal Articles by
Author Zhenghan Fang

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Automatic brain extraction from 3D fetal MR image with deep learning-based multi-step framework.

Jian Chen, Zhenghan Fang, Guofu Zhang, Lei Ling, Gang Li, He Zhang, Li Wang,

Brain extraction is a fundamental prerequisite step in neuroimage analysis for fetus. Due to surrounding maternal tissues and unpredictable movement, brain extraction from fetal Magnetic Resonance (MR) images is a challenging task. In this paper, we propose a novel deep learning-based multi-step framework for brain extraction from 3D fetal MR ... Read more >>

Comput Med Imaging Graph (Computerized medical imaging and graphics : the official journal of the Computerized Medical Imaging Society)
[2020, 88:101848]

Cited: 0 times

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Using Artificial Intelligence to Detect COVID-19 and Community-acquired Pneumonia Based on Pulmonary CT: Evaluation of the Diagnostic Accuracy.

Lin Li, Lixin Qin, Zeguo Xu, Youbing Yin, Xin Wang, Bin Kong, Junjie Bai, Yi Lu, Zhenghan Fang, Qi Song, Kunlin Cao, Daliang Liu, Guisheng Wang, Qizhong Xu, Xisheng Fang, Shiqin Zhang, Juan Xia, Jun Xia,

Background Coronavirus disease 2019 (COVID-19) has widely spread all over the world since the beginning of 2020. It is desirable to develop automatic and accurate detection of COVID-19 using chest CT. Purpose To develop a fully automatic framework to detect COVID-19 using chest CT and evaluate its performance. Materials and ... Read more >>

Radiology (Radiology)
[2020, 296(2):E65-E71]

Cited: 57 times

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Submillimeter MR fingerprinting using deep learning-based tissue quantification.

Zhenghan Fang, Yong Chen, Sheng-Che Hung, Xiaoxia Zhang, Weili Lin, Dinggang Shen,

<h4>Purpose</h4>To develop a rapid 2D MR fingerprinting technique with a submillimeter in-plane resolution using a deep learning-based tissue quantification approach.<h4>Methods</h4>A rapid and high-resolution MR fingerprinting technique was developed for brain T<sub>1</sub> and T<sub>2</sub> quantification. The 2D acquisition was performed using a FISP-based MR fingerprinting sequence and a spiral trajectory with ... Read more >>

Magn Reson Med (Magnetic resonance in medicine)
[2020, 84(2):579-591]

Cited: 2 times

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RCA-U-Net: Residual Channel Attention U-Net for Fast Tissue Quantification in Magnetic Resonance Fingerprinting.

Zhenghan Fang, Yong Chen, Dong Nie, Weili Lin, Dinggang Shen,

Magnetic resonance fingerprinting (MRF) is a relatively new imaging framework which allows rapid and simultaneous quantification of multiple tissue properties, such as T1 and T2 relaxation times, in one acquisition. To accelerate the data sampling in MRF, a variety of methods have been proposed to extract tissue properties from highly ... Read more >>

Med Image Comput Comput Assist Interv (Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention)
[2019, 11766:101-109]

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High-resolution 3D MR Fingerprinting using parallel imaging and deep learning.

Yong Chen, Zhenghan Fang, Sheng-Che Hung, Wei-Tang Chang, Dinggang Shen, Weili Lin,

MR Fingerprinting (MRF) is a relatively new imaging framework capable of providing accurate and simultaneous quantification of multiple tissue properties for improved tissue characterization and disease diagnosis. While 2D MRF has been widely available, extending the method to 3D MRF has been an actively pursued area of research as a ... Read more >>

Neuroimage (NeuroImage)
[2020, 206:116329]

Cited: 1 time

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Deep Learning for Fast and Spatially Constrained Tissue Quantification From Highly Accelerated Data in Magnetic Resonance Fingerprinting.

Zhenghan Fang, Yong Chen, Mingxia Liu, Lei Xiang, Qian Zhang, Qian Wang, Weili Lin, Dinggang Shen,

Magnetic resonance fingerprinting (MRF) is a quantitative imaging technique that can simultaneously measure multiple important tissue properties of human body. Although MRF has demonstrated improved scan efficiency as compared to conventional techniques, further acceleration is still desired for translation into routine clinical practice. The purpose of this paper is to ... Read more >>

IEEE Trans Med Imaging (IEEE transactions on medical imaging)
[2019, 38(10):2364-2374]

Cited: 3 times

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Deep Learning for Fast and Spatially-Constrained Tissue Quantification from Highly-Undersampled Data in Magnetic Resonance Fingerprinting (MRF).

Zhenghan Fang, Yong Chen, Mingxia Liu, Yiqiang Zhan, Weili Lin, Dinggang Shen,

Magnetic resonance fingerprinting (MRF) is a novel quantitative imaging technique that allows simultaneous measurements of multiple important tissue properties in human body, e.g., T1 and T2 relaxation times. While MRF has demonstrated better scan efficiency as compared to conventional quantitative imaging techniques, further acceleration is desired, especially for certain subjects ... Read more >>

Mach Learn Med Imaging (Machine learning in medical imaging. MLMI (Workshop))
[2018, 11046:398-405]

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Quantification of relaxation times in MR Fingerprinting using deep learning.

Zhenghan Fang, Yong Chen, Weili Lin, Dinggang Shen,

MRF is a new quantitative MR imaging technique, which can provide rapid and simultaneous measurement of multiple tissue properties. Compared to the fast speed for data acquisition, the post-processing to extract tissue properties with MRF is relatively slow and often requires a large memory for the storage of both image ... Read more >>

Proc Int Soc Magn Reson Med Sci Meet Exhib Int Soc Magn Reson Med Sci Meet Exhib (Proceedings of the International Society for Magnetic Resonance in Medicine ... Scientific Meeting and Exhibition. International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition)
[2017, 25:]

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