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Ling, Ronghua; Wang, Min; Lu, Jiaying; Wu, Shaoyou; Wu, Ping; Ge, Jingjie; Wang, Luyao; Liu, Yingqian; Jiang, Juanjuan; Shi, Kuangyu; Yan, Zhuangzhi; Zuo, Chuantao; Jiang, Jiehui (2024). Radiomics-Guided Deep Learning Networks Classify Differential Diagnosis of Parkinsonism. Brain Sciences, 14(7) MDPI 10.3390/brainsci14070680
Wang, Min; Schutte, Michael; Grimmer, Timo; Lizarraga, Aldana; Schultz, Thomas; Hedderich, Dennis M; Diehl-Schmid, Janine; Rominger, Axel; Ziegler, Sybille; Navab, Nassir; Yan, Zhuangzhi; Jiang, Jiehui; Yakushev, Igor; Shi, Kuangyu (2022). Reducing instability of inter-subject covariance of FDG uptake networks using structure-weighted sparse estimation approach. European journal of nuclear medicine and molecular imaging, 50(1), pp. 80-89. Springer 10.1007/s00259-022-05949-9
Wang, Min; Cui, Bixiao; Shan, Yi; Yang, Hongwei; Yan, Zhuangzhi; Sundar, Lalith Kumar Shiyam; Alberts, Ian; Rominger, Axel; Wendler, Thomas; Shi, Kuangyu; Ma, Yan; Jiang, Jiehui; Lu, Jie (2022). Non-Invasive Glucose Metabolism Quantification Method Based on Unilateral ICA Image Derived Input Function by Hybrid PET/MR in Ischemic Cerebrovascular Disease. IEEE journal of biomedical and health informatics, 26(10), pp. 5122-5129. Institute of Electrical and Electronics Engineers 10.1109/JBHI.2022.3193190
Wang, Min; Jiang, Jiehui; Yan, Zhuangzhi; Alberts, Ian; Ge, Jingjie; Zhang, Huiwei; Zuo, Chuantao; Yu, Jintai; Rominger, Axel; Shi, Kuangyu (2020). Individual brain metabolic connectome indicator based on Kullback-Leibler Divergence Similarity Estimation predicts progression from mild cognitive impairment to Alzheimer's dementia. European journal of nuclear medicine and molecular imaging, 47(12), pp. 2753-2764. Springer-Verlag 10.1007/s00259-020-04814-x
Shen, Ting; Jiang, Jiehui; Lin, Wei; Ge, Jingjie; Wu, Ping; Zhou, Yongjin; Zuo, Chuantao; Wang, Jian; Yan, Zhuangzhi; Shi, Kuangyu (2019). Use of Overlapping Group LASSO Sparse Deep Belief Network to Discriminate Parkinson's Disease and Normal Control. Frontiers in neuroscience, 13(396), p. 396. Frontiers Research Foundation 10.3389/fnins.2019.00396
