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  1. Article ; Online: A robust seizure detection and prediction method with feature selection and spatio-temporal casual neural network model.

    Zhang, Yuanming / Li, Xin / Wang, Shuang / Shen, Haibin / Huang, Kejie

    Journal of neural engineering

    2023  Volume 20, Issue 5

    Abstract: Objective. ...

    Abstract Objective.
    MeSH term(s) Child ; Humans ; Seizures/diagnosis ; Epilepsy/diagnosis ; Neural Networks, Computer ; Algorithms ; Brain ; Electroencephalography/methods
    Language English
    Publishing date 2023-10-18
    Publishing country England
    Document type Journal Article
    ZDB-ID 2170901-4
    ISSN 1741-2552 ; 1741-2560
    ISSN (online) 1741-2552
    ISSN 1741-2560
    DOI 10.1088/1741-2552/acfff5
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 6071: Show issues Location:
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    bis Jg. 2021: Bestellungen von Artikeln über das Online-Bestellformular
    ab Jg. 2022: Lesesaal (EG)

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  2. Article ; Online: Micro-double-port endoscopic thoracic sympathectomy for treatment of primary palmar hyperhidrosis

    LIU Xuehai / LI Yanning / WANG Jianglong / HUANG Kejie / LI Kun

    陆军军医大学学报, Vol 44, Iss 13, Pp 1390-

    report of 25 cases

    2022  Volume 1394

    Abstract: Objective To summarize the clinical application of micro-double-port endoscopic thoracic sympathectomy in treatment of primary palmar hyperhidrosis. Methods Clinical data of 25 patients with primary palmar hyperhidrosis undergoing sympathectomy in our ... ...

    Abstract Objective To summarize the clinical application of micro-double-port endoscopic thoracic sympathectomy in treatment of primary palmar hyperhidrosis. Methods Clinical data of 25 patients with primary palmar hyperhidrosis undergoing sympathectomy in our department from April 2021 to March 2022 were collected and retrospectively analyzed. They were 9 males and 16 females, at an age of 23.0±5.1 (15, 35) years. During the operation, two 0.5-cm incisions were made at the anterior axillary line and the mid-axillary line of the 3rd or 4th intercostal space, then two 5-mm trocars were placed, and a 5-mm needle-type thoracoscope was used to establish an artificial pneumothorax. R3 and R4 thoracic sympathetic chains were transected. Results All 25 patients successfully received the operation and were discharged upon recovery. One patient developed a small amount of pneumothorax on the right side after operation, and re-examination with chest X-ray filming showed that the pneumothorax was absorbed in 12 d after operation. The symptoms of hyperhidrosis on the hands all disappeared, and hand temperature was increased as expected. The operation time was 23.2±4.7 min, the intraoperative blood loss was 4.2±2.3 mL, the postoperative hospital stay was 0.6±0.4 d, and the postoperative pain score was 1.0±0.6. The treatment effective rate was 100%, and the satisfaction of outcome was 100%. Fifteen patients had mild compensatory hyperhidrosis postoperatively. Conclusion In treatment of primary palmar hyperhidrosis, micro-double-port endoscopic thoracic sympathectomy is characterized by small incision, safe and easy operation, short operation time and postoperative hospital stay, and no obvious pain and more satisfying outcomes.
    Keywords micro-double-port approach ; primary palmar hyperhidrosis ; video-assisted thoracoscopy ; endoscopic thoracic sympathectomy ; Medicine (General) ; R5-920
    Subject code 616
    Language Chinese
    Publishing date 2022-07-01T00:00:00Z
    Publisher Editorial Office of Journal of Army Medical University
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Book ; Online ; Thesis: Lernen, Chinese zu werden

    Huang, Kejie [Verfasser]

    Eine Fallstudie über die selektive Rekonstruktion der ethnischen Identität chinesischer Zuwanderer

    2018  

    Author's details Kejie Huang
    Keywords Erziehung, Schul- und Bildungswesen ; Education
    Subject code sg370
    Language German
    Publisher Nomos Verlagsgesellschaft mbH & Co. KG
    Publishing place Baden-Baden
    Document type Book ; Online ; Thesis
    ISBN 978-3-8452-8806-2 ; 3-8452-8806-X
    Database Digital theses on the web

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  4. Article: Relations between physical activity and hippocampal functional connectivity: Modulating role of mind wandering.

    Shi, Donglin / Geng, Fengji / Hao, Xiaoxin / Huang, Kejie / Hu, Yuzheng

    Frontiers in human neuroscience

    2022  Volume 16, Page(s) 950893

    Abstract: Physical activity is critical for maintaining cognitive and brain health. Previous studies have indicated that the effect of physical activity on cognitive and brain function varies between individuals. The present study aimed to examine whether mind ... ...

    Abstract Physical activity is critical for maintaining cognitive and brain health. Previous studies have indicated that the effect of physical activity on cognitive and brain function varies between individuals. The present study aimed to examine whether mind wandering modulated the relations between physical activity and resting-state hippocampal functional connectivity. A total of 99 healthy adults participated in neuroimaging data collection as well as reported their physical activity in the past week and their propensity to mind wandering during typical activities. The results indicated that mind wandering was negatively related to the resting-state functional connectivity between hippocampus and right inferior occipital gyrus. Additionally, for participants with higher level of mind wandering, physical activity was negatively related to hippocampal connectivity at left precuneus and right precentral gyrus. In contrast, such relations were positive at right medial frontal gyrus and bilateral precentral gyrus for participants with lower level of mind wandering. Altogether, these findings indicated that the relations between physical activity and hippocampal functional connectivity vary as a function of mind wandering level, suggesting that individual differences are important to consider when we aim to maintain or improve cognitive and brain health through increasing physical activity.
    Language English
    Publishing date 2022-10-03
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2425477-0
    ISSN 1662-5161
    ISSN 1662-5161
    DOI 10.3389/fnhum.2022.950893
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  5. Article ; Online: A Semi-Supervised Few-Shot Learning Model for Epileptic Seizure Detection.

    Zhang, Zheng / Li, Xin / Geng, Fengji / Huang, Kejie

    Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference

    2021  Volume 2021, Page(s) 600–603

    Abstract: In the past decade, the rapid development of machine learning has dramatically improved the performance of epileptic detection with Electroencephalography (EEG). However, only a small amount of labeled epileptic data is available for training because ... ...

    Abstract In the past decade, the rapid development of machine learning has dramatically improved the performance of epileptic detection with Electroencephalography (EEG). However, only a small amount of labeled epileptic data is available for training because labeling requires numerous neurologists. This paper proposes a one-step semi-supervised epilepsy detection system to reduce the labeling cost by fully utilizing the unlabeled data. The proposed neural network training strategy enables a more robust and accurate decision boundary by forcing the consistency of the double predictions on the same unlabeled data. The results show that the Area Under Receiver Operating Characteristic (AUROC) curves of our proposed model are 10.3% and 4.9% higher than the supervised methods on CHB-MIT and Kaggle datasets, respectively.
    MeSH term(s) Electroencephalography ; Epilepsy/diagnosis ; Humans ; Neural Networks, Computer ; Seizures/diagnosis ; Supervised Machine Learning
    Language English
    Publishing date 2021-12-10
    Publishing country United States
    Document type Journal Article
    ISSN 2694-0604
    ISSN (online) 2694-0604
    DOI 10.1109/EMBC46164.2021.9630363
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  6. Article ; Online: Relations of Creativity to the Interplay Between High-order Cognitive Functions: Behavioral and Neural Evidence.

    Hao, Xiaoxin / Geng, Fengji / Wang, Tengfei / Hu, Yuzheng / Huang, Kejie

    Neuroscience

    2021  Volume 473, Page(s) 90–101

    Abstract: As a high-order cognitive ability, creativity is viewed as the result of complex interplay between a set of mental processes. However, previous studies have mainly tested one-to-one mutual relations between creativity and other cognitive abilities. It ... ...

    Abstract As a high-order cognitive ability, creativity is viewed as the result of complex interplay between a set of mental processes. However, previous studies have mainly tested one-to-one mutual relations between creativity and other cognitive abilities. It lacks studies to examine whether creativity is related to the interaction between cognitive systems. The current study aimed to fill this gap by testing the relations of creativity to the interactions between cognitive control and episodic memory systems using both behavioral and neuroimaging methods. The Alternative Uses Task was used to measure the divergent component of creativity. A computer-based behavioral task was used to measure cognitive control, episodic memory, and their interactions. Additionally, the interactions between cognitive systems were characterized by computing the resting-state functional connectivity between hippocampus and prefrontal regions, which are the neural substrates for episodic memory and cognitive control, respectively. By analyzing these behavioral and neuroimaging data, the behavioral results indicated that creativity was significantly related to the effect of cognitive control induced by switching tasks or proactive cues on subsequent memories of items or sources. Additionally, neuroimaging results showed that creativity was significantly related to the connectivity from hippocampus to both left superior frontal gyrus and middle frontal gyrus. Such relations were also differentiated between anterior and posterior hippocampus. Altogether, these findings suggest that creativity is related to interactions between cognitive control and episodic memory, supporting the claim that creativity is the result of complex interplay between high-order cognitive functions.
    MeSH term(s) Brain/diagnostic imaging ; Brain Mapping ; Cognition ; Creativity ; Magnetic Resonance Imaging ; Memory, Episodic
    Language English
    Publishing date 2021-08-24
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 196739-3
    ISSN 1873-7544 ; 0306-4522
    ISSN (online) 1873-7544
    ISSN 0306-4522
    DOI 10.1016/j.neuroscience.2021.08.015
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    Zs.A 1215: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
    bis Jg. 1994: Bestellungen von Artikeln über das Online-Bestellformular
    Jg. 1995 - 2021: Lesesall (1.OG)
    ab Jg. 2022: Lesesaal (EG)

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  7. Article ; Online: MsVRL: Self-Supervised Multiscale Visual Representation Learning via Cross-Level Consistency for Medical Image Segmentation.

    Zheng, Ruifeng / Zhong, Ying / Yan, Senxiang / Sun, Hongcheng / Shen, Haibin / Huang, Kejie

    IEEE transactions on medical imaging

    2022  Volume 42, Issue 1, Page(s) 91–102

    Abstract: Automated medical image segmentation for organs or lesions plays an essential role in clinical diagnoses and treatment plannings. However, training an accurate and robust segmentation model is still a long-standing challenge due to the time-consuming and ...

    Abstract Automated medical image segmentation for organs or lesions plays an essential role in clinical diagnoses and treatment plannings. However, training an accurate and robust segmentation model is still a long-standing challenge due to the time-consuming and expertise-intensive annotations for training data, especially 3-D medical images. Recently, self-supervised learning emerges as a promising approach for unsupervised visual representation learning, showing great potential to alleviate the expertise annotations for medical images. Although global representation learning has attained remarkable results on iconic datasets, such as ImageNet, it can not be applied directly to medical image segmentation, because the segmentation task is non-iconic, and the targets always vary in physical scales. To address these problems, we propose a Multi-scale Visual Representation self-supervised Learning (MsVRL) model, to perform finer-grained representation and deal with different target scales. Specifically, a multi-scale representation conception, a canvas matching method, an embedding pre-sampling module, a center-ness branch, and a cross-level consistent loss are introduced to improve the performance. After pre-trained on unlabeled datasets (RibFrac and part of MSD), MsVRL performs downstream segmentation tasks on labeled datasets (BCV, spleen of MSD, and KiTS). Results of the experiments show that MsVRL outperforms other state-of-the-art works on these medical image segmentation tasks.
    MeSH term(s) Spleen ; Image Processing, Computer-Assisted ; Supervised Machine Learning
    Language English
    Publishing date 2022-12-29
    Publishing country United States
    Document type Journal Article ; Research Support, Non-U.S. Gov't
    ZDB-ID 622531-7
    ISSN 1558-254X ; 0278-0062
    ISSN (online) 1558-254X
    ISSN 0278-0062
    DOI 10.1109/TMI.2022.3204551
    Database MEDical Literature Analysis and Retrieval System OnLINE

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    Zs.A 2546: Show issues Location:
    Je nach Verfügbarkeit (siehe Angabe bei Bestand)
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    Jg. 1995 - 2021: Lesesall (2.OG)
    ab Jg. 2022: Lesesaal (EG)

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  8. Article: KLF4 loss in hepatocellular carcinoma: Improving prognostic prediction and correlating immune infiltrates.

    Chen, Desheng / Zhu, Qi / Li, Tiewen / Fan, Xuhui / Lou, Yichao / Zhang, Yi / Huang, Kejie / Sun, Hongcheng

    Frontiers in genetics

    2023  Volume 14, Page(s) 1106952

    Abstract: Introduction: ...

    Abstract Introduction:
    Language English
    Publishing date 2023-03-02
    Publishing country Switzerland
    Document type Journal Article
    ZDB-ID 2606823-0
    ISSN 1664-8021
    ISSN 1664-8021
    DOI 10.3389/fgene.2023.1106952
    Database MEDical Literature Analysis and Retrieval System OnLINE

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  9. Book ; Online: Thermal Infrared Image Inpainting via Edge-Aware Guidance

    Wang, Zeyu / Shen, Haibin / Men, Changyou / Sun, Quan / Huang, Kejie

    2022  

    Abstract: Image inpainting has achieved fundamental advances with deep learning. However, almost all existing inpainting methods aim to process natural images, while few target Thermal Infrared (TIR) images, which have widespread applications. When applied to TIR ... ...

    Abstract Image inpainting has achieved fundamental advances with deep learning. However, almost all existing inpainting methods aim to process natural images, while few target Thermal Infrared (TIR) images, which have widespread applications. When applied to TIR images, conventional inpainting methods usually generate distorted or blurry content. In this paper, we propose a novel task -- Thermal Infrared Image Inpainting, which aims to reconstruct missing regions of TIR images. Crucially, we propose a novel deep-learning-based model TIR-Fill. We adopt the edge generator to complete the canny edges of broken TIR images. The completed edges are projected to the normalization weights and biases to enhance edge awareness of the model. In addition, a refinement network based on gated convolution is employed to improve TIR image consistency. The experiments demonstrate that our method outperforms state-of-the-art image inpainting approaches on FLIR thermal dataset.
    Keywords Computer Science - Computer Vision and Pattern Recognition ; Computer Science - Artificial Intelligence
    Subject code 006
    Publishing date 2022-10-28
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Book ; Online: A Reconfigurable Convolution-in-Pixel CMOS Image Sensor Architecture

    Song, Ruibing / Huang, Kejie / Wang, Zongsheng / Shen, Haibin

    2021  

    Abstract: The separation of the data capture and analysis in modern vision systems has led to a massive amount of data transfer between the end devices and cloud computers, resulting in long latency, slow response, and high power consumption. Efficient hardware ... ...

    Abstract The separation of the data capture and analysis in modern vision systems has led to a massive amount of data transfer between the end devices and cloud computers, resulting in long latency, slow response, and high power consumption. Efficient hardware architectures are under focused development to enable Artificial Intelligence (AI) at the resource-limited end sensing devices. One of the most promising solutions is to enable Processing-in-Pixel (PIP) scheme. However, the conventional schemes suffer from the low fill-factor issue. This paper proposes a PIP based CMOS sensor architecture, which allows convolution operation before the column readout circuit to significantly improve the image reading speed with much lower power consumption. The simulation results show that the proposed architecture could support the computing efficiency up to 11.65 TOPS/W at the 8-bit weight configuration, which is three times as high as the conventional schemes. The transistors required for each pixel are only 2.5T, significantly improving the fill-factor.
    Keywords Electrical Engineering and Systems Science - Image and Video Processing ; Computer Science - Machine Learning
    Subject code 620
    Publishing date 2021-01-09
    Publishing country us
    Document type Book ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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