Shuheng Zhang

Inner Mongolia University of Science and Technology

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Jiwei Bai

Beijing Tian Tan Hospital

Yixuan Zhai

Guangzhou Medical University

Mingxuan Li

Tianjin Agricultural University

Chuzhong Li

Beijing Institute of Neurosurgery

Fiona C. Meldrum

University of Leeds

Yazhuo Zhang

Second People's Hospital of Yunnan Province

Stéphane Veesler

Centre National de la Recherche Scientifique

Shuai Wang

Capital Medical University

Nadine Candoni

Centre Interdisciplinaire de Nanoscience de Marseille

Qiang He

Northeastern University

Cooperative Institutions

Chinese Academy of Sciences

Zhejiang University

Shanghai Jiao Tong University

University of Chinese Academy of Sciences

Capital Medical University

Sichuan University

Huazhong University of Science and Technology

Shenzhen Institutes of Advanced Technology

Wuhan University

Chinese Academy of Medical Sciences & Peking Union Medical College

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Bone metastasis automatic segmentation from [¹⁸F]NaF whole-body PET using a convolutional neural network

Junyu Dong Zhihua Huang Shuheng Zhang Y. Chen Vladimir Stanković

Whole-body [ ¹⁸ F]NaF positron emission tomography has attracted growing attention for its extremely sensitive bone imaging performance and outstanding diagnostic efficacy in identifying bone metastases during both the staging and restaging processes for patients with high-risk cancer. However, segmentation for whole-body imaging data is heavy and time-consuming work for radiologists and manual segmentation can leave out suspicious metastatic lesions. To utilize the automatic segmentation of suspicious bone metastatic lesions from [ ¹⁸ F]NaF positron emission tomography, we explore convolutional neural network-based deep learning techniques to achieve an end-to-end segmentation method. The network was trained from the input [ ¹⁸ F]NaF positron emission tomography standard uptake value image to produce a corresponding segmentation mask. The performance of the issued segmentation method was evaluated by typical segmentation criteria including precision, recall, F1-score and intersection over union. The quality of neural network-produced segmentation masks is good in general, and it showed the potential to assist clinicians and radiologists and simplify the process of segmentation substantially.

10.1109/nssmicrtsd49126.2023.10338500

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Integrative Approaches to Soybean Resilience, Productivity, and Utility: A Review of Genomics, Computational Modeling, and Economic Viability

Plants (2025)

Yu-Hong Gai Shu-Hao Liu Zhidan Zhang Jian Wei Hongtao Wang

Soybean is a vital crop globally and a key source of food, feed, and biofuel. With advancements in high-throughput technologies, soybeans have become a key target for genetic improvement. This comprehensive review explores advances in multi-omics, artificial intelligence, and economic sustainability to enhance soybean resilience and productivity. Genomics revolution, including marker-assisted selection (MAS), genomic selection (GS), genome-wide association studies (GWAS), QTL mapping, GBS, and CRISPR-Cas9, metagenomics, and metabolomics have boosted the growth and development by creating stress-resilient soybean varieties. The artificial intelligence (AI) and machine learning approaches are improving genetic trait discovery associated with nutritional quality, stresses, and adaptation of soybeans. Additionally, AI-driven technologies like IoT-based disease detection and deep learning are revolutionizing soybean monitoring, early disease identification, yield prediction, disease prevention, and precision farming. Additionally, the economic viability and environmental sustainability of soybean-derived biofuels are critically evaluated, focusing on trade-offs and policy implications. Finally, the potential impact of climate change on soybean growth and productivity is explored through predictive modeling and adaptive strategies. Thus, this study highlights the transformative potential of multidisciplinary approaches in advancing soybean resilience and global utility.

Resilience

10.3390/plants14050671

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Deepfusion Encoder for Unsupervised Monocular Metric Depth Estimation

Zhihua Huang Mohammed A. H. Ali Y. Nukman Haixia Xu Hui Chen

Monocular

10.2139/ssrn.5040802

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Controlling the fluorescence and room-temperature phosphorescence behaviour of carbon nanodots with inorganic crystalline nanocomposites

Nature Communications (2019)

David C. Green Mark A. Holden Mark A. Levenstein Shuheng Zhang Benjamin Johnson

Abstract There is a significant drive to identify alternative materials that exhibit room temperature phosphorescence for technologies including bio-imaging, photodynamic therapy and organic light-emitting diodes. Ideally, these materials should be non-toxic and cheap, and it will be possible to control their photoluminescent properties. This was achieved here by embedding carbon nanodots within crystalline particles of alkaline earth carbonates, sulphates and oxalates. The resultant nanocomposites are luminescent and exhibit a bright, sub-second lifetime afterglow. Importantly, the excited state lifetimes, and steady-state and afterglow colours can all be systematically controlled by varying the cations and anions in the host inorganic phase, due to the influence of the cation size and material density on emissive and non-emissive electronic transitions. This simple strategy provides a flexible route for generating materials with specific, phosphorescent properties and is an exciting alternative to approaches relying on the synthesis of custom-made luminescent organic molecules.

Nanodot

10.1038/s41467-018-08214-6

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Citations (140)

Densities and Viscosities of the Binary Mixtures of 1-Ethyl-3-methylimidazolium Bis(trifluoromethylsulfonyl)imide with N-Methyl-2-pyrrolidone or Ethanol at T = (293.15 to 323.15) K

Journal of Chemical & Engineering Data (2012)

Hongwei Yao Shuheng Zhang Jieli Wang Qing Zhou Haifeng Dong

The densities and viscosities of 1-ethyl-3-methylimidazolium bis(trifluoromethylsulfonyl)imide ([EMIM][NTf2]) + N-methyl-2-pyrrolidone (NMP) and [EMIM][NTf2] + ethanol mixtures were investigated over the mole fraction range from (0.1 to 0.9) and at temperatures from (293.15 to 323.15) K at intervals of 5 K. The densities can be well-represented by the quadratic equation, and the viscosities can be represented in the form of the Vogel equation. The excess molar volumes (VE) and viscosity deviations (Δη) were calculated, and the results were fitted to the Redlich–Kister equation using a multiparametric nonlinear regression method. The estimated parameters of the Redlich–Kister equation and standard deviation were also presented. The results showed that the densities and viscosities were dependent strongly on NMP or ethanol content. Comparatively, the viscosity deviation Δη was more sensitive to temperature than the excess molar volume VE.

Mole fraction

Imide

Absolute deviation

10.1021/je200922s

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Citations (67)

Mean platelet volume and platelet distribution width serve as prognostic biomarkers in skull base chordoma: a retrospective study

BMC Cancer (2020)

Mingxuan Li Jiwei Bai Shuai Wang Yixuan Zhai Shuheng Zhang

Abstract Background Increasing studies have demonstrated that activated platelets play an essential role in tumour progression. However, the level and prognostic role of platelet indices in chordoma patients remain unclear. The aim of the current study was to characterize the prognostic performance of platelet count (PLT), mean platelet volume (MPV) and platelet distribution width (PDW) in skull base chordoma patients. Methods 187 primary skull base chordoma patients between January 2008 and September 2014 were enrolled in this retrospective study. The optimal cut-off values were determined by X-tile software, and the correlations between PLT, MPV, PDW and clinicopathological features were further analysed. Kaplan-Meier curve and Cox regression analysis were used for survival analysis. Results The values of preoperative PTL, MPV and PDW ranged from 104 to 501 × 10 9 /L, 6.7 to 14.2 fl, and 7.8 to 26.2%, respectively. Elevated PLT was associated with larger tumour volume ( p = 0.002). Kaplan-Meier survival analysis revealed that increased MPV and PDW were associated with shorter overall survival ( p = 0.022 and 0.008, respectively). Importantly, multivariate Cox analysis demonstrated that elevated PDW was an independent unfavourable predictive factor for overall survival (hazard ratio (HR), 2.154, 95% confidence interval (CI), 1.258–3.688, p = 0.005). Conclusions Our data show that elevated MPV and PDW are associated with poor outcomes in skull base chordoma and that PDW may be helpful to identify patients with high risk.

Chordoma

Mean platelet volume

10.1186/s12885-020-07497-7

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Study on the influence of different scanning directions of whole-body MRI on the detection of lesions

Proceedings on CD-ROM - International Society for Magnetic Resonance in Medicine. Scientific Meeting and Exhibition/Proceedings of the International Society for Magnetic Resonance in Medicine, Scientific Meeting and Exhibition (2024)

Nan Wang Ailian Liu Guobin Li Shuheng Zhang Shaoxin Xiang

Whole-body MRI (WB-MRI) is proposed as a potential modality to evaluate the entire body with excellent spatial resolution and high sensitivity. However, the long scanning time of WB-MRI has still limited the clinical application. This study compared the time cost and lesion display effect of WB-MRI in different scan directions. This study demonstrated that using coronal scanning in WB-MRI is an effective method to reduce the scan time and achieve good performance in detecting lesions in clinical applications.

Modality (human–computer interaction)

Real-time MRI

10.58530/2023/1505

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Effects of Bioorganic Fertilizers on the Leaf Antioxidant Enzyme Activity and the Photosynthetic Characteristics of Replanted Szechuan Pepper, Zanthoxylum simulans

Journal of Agricultural Science and Technology B (2020)

Shuheng Zhang Jing He Bin Wang Xiaoyan Zhang Qi Liu

Zanthoxylum

Bioorganic chemistry

10.17265/2161-6264/2020.04.005

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Utilization of high resolution and low velocity encoding PCA with highly accelerated compressed sensing for preoperative SEEG planning

Qiangqiang Liu Shuheng Zhang Jiwen Xu Jiachen Zhu Yiwen Shen

It is essential to avoid small vessels during stereo-electroencephalography (SEEG) electrode implantation. In this study, we proposed a 6-fold Compressed sensing accelerated, 5cm/s Low velocity encoded, 0.75mm Isotropic resolution Phase contrast Magnetic Resonance Angiography (CLIP-MRA). In CLIP-MRA, the compressed sensing based acceleration method was shown to achieve better image quality or shorter scan duration compared to parallel imaging based acceleration. CLIP-MRA was able to display not only cortical arteries and veins simultaneously, but also vessels in the skull. Safety and effectiveness of CLIP-MRA utilized preoperative SEEG planning were evaluated on a small patient cohort.

Stereoelectroencephalography

Magnetic resonance angiography

10.58530/2022/4395

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What makes a good data augmentation for few-shot unsupervised image anomaly detection?

arXiv (Cornell University) (2023)

Shuheng Zhang Lingrui Zhang Guoyang Xie Jiaqi Liu Hua Yan

Data augmentation is a promising technique for unsupervised anomaly detection in industrial applications, where the availability of positive samples is often limited due to factors such as commercial competition and sample collection difficulties. In this paper, how to effectively select and apply data augmentation methods for unsupervised anomaly detection is studied. The impact of various data augmentation methods on different anomaly detection algorithms is systematically investigated through experiments. The experimental results show that the performance of different industrial image anomaly detection (termed as IAD) algorithms is not significantly affected by the specific data augmentation method employed and that combining multiple data augmentation methods does not necessarily yield further improvements in the accuracy of anomaly detection, although it can achieve excellent results on specific methods. These findings provide useful guidance on selecting appropriate data augmentation methods for different requirements in IAD.

Anomaly (physics)

Sample (material)

10.48550/arxiv.2304.03294

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