检索结果-内蒙古大学图书馆

arXiv 2025年

作者： Qu, Linhao Li, Shiman Luo, Xiaoyuan Liu, Shaolei Guo, Qinhao Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University Shanghai China Shanghai Key Lab of Medical Image Computing and Computer Assisted Intervention Shanghai China Department of Gynecologic Oncology Shanghai Cancer Center Fudan University Shanghai China Department of Oncology Shanghai Medical College Fudan University Shanghai China

computer-aided Whole Slide image (WSI) classification has the potential to enhance the accuracy and efficiency of clinical pathological diagnosis. It is commonly formulated as a Multiple Instance Learning (MIL) problem, where each WSI is treated as a bag and the small patches extracted from the WSI are considered instances within that bag. However, obtaining labels for a large number of bags is a costly and time-consuming process, particularly when utilizing existing WSIs for new classification tasks. This limitation renders most existing WSI classification methods ineffective. To address this issue, we propose a novel WSI classification problem setting, more aligned with clinical practice, termed Weakly Semi-supervised Whole slide image Classification (WSWC). In WSWC, a small number of bags are labeled, while a significant number of bags remain unlabeled. The MIL nature of the WSWC problem, coupled with the absence of patch labels, distinguishes it from typical semi-supervised image classification problems, making existing algorithms for natural images unsuitable for directly solving the WSWC problem. In this paper, we present a concise and efficient framework, named CroCo, to tackle the WSWC problem through two-level Cross Consistency supervision. CroCo comprises two heterogeneous classifier branches capable of performing both instance classification and bag classification. The fundamental idea is to establish cross-consistency supervision at both the bag-level and instance-level between the two branches during training. Extensive experiments conducted on four datasets demonstrate that CroCo achieves superior bag classification and instance classification performance compared to other comparative methods when limited WSIs with bag labels are available. To the best of our knowledge, this paper presents for the first time the WSWC problem and gives a successful resolution. Copyright © 2025, The Authors. All rights reserved.

关键词： Semi-supervised learning

来源：评论

学校读者我要写书评

暂无评论

Catalpol ameliorates depressive-like behaviors in CUMS mice via oxidative stress-mediated NLRP3 inflammasome and neuroinflammation

Catalpol ameliorates depressive-like behaviors in CUMS mice ...

引用

中国解剖学会2021年年会

作者： Wu Haoran Wang Yalin Hu Juntao Department of Anatomy Histology and EmbryologyDepartment of Integrative Medicine and NeurobiologySchool of Basic Medical SciencesInstitutes of Brain ScienceState Key Laboratory of Medical Neurobiology and Collaborative Innovation Center for Brain ScienceShanghai Medical CollegeFudan University.Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai

The purpose of the present study was to investigate whether catalpol exhibited neuro-protective effects in chronic unpredictable mild stress (CUMS) mice through oxidative stress-mediated nucleotide-binding oligomeriza... 详细信息

关键词： Catalpol ameliorates depressive-like behaviors in CUMS mice via oxidative stress-mediated NLRP3 inflammasome and neuroinflammation

来源：评论

学校读者我要写书评

暂无评论

Prohibitin(PHB)interacts with AKT in mitochondria to coordinately modulate sperm motility

引用

Asian Journal of Andrology 2020年第6期22卷 583-589页

作者： Xiao-Hui Li Ran-Ran Chai Guo-Wu Chen Ling-Fei Zhang Wen-Jing Tan-Tai Hui-Juan Shi Patricia A Martin-DeLeon Wai-Sum O Hong Chen Department of Anatomy Histology and EmbryologyKey Laboratory of Medical Imaging Computing and Computer Assisted Intervention of ShanghaiSchool of Basic Medical SciencesShanghai Medical CollegeFudan UniversityShanghai 200032China Shanghai Ji'Ai Genetics and IVF Institute Obstetrics and Gynecology HospitalInstitute of Reproduction and DevelopmentFudan UniversityShanghai 200011China Key Lab of Reproduction Regulation of NPFPC-Shanghai Institute of Planned Parenthood Research Fudan University Reproduction and Development InstitutionShanghai 200032China Department of Biological Sciences University of DelawareNewarkDE 19716-2590USA School of Biomedical Sciences The University of Hong KongHong Kong SARChina

Prohibitin(PHB),an evoluti on arily con served mitochondrial inner membra ne protein,is highly expressed in cells that require strong mitoch on drial ***,we dem on strated that the deleti on of Phb in spermatocytes results in impaired mitochondrial *** addition,PHB expression in the mitochondrial sheath of human sperm has a significantly negative correlation with mitochondrial reactive oxygen species levels,but a positive one with mitochondrial membrane potential and sperm *** results suggest that mitochondrial PHB expression plays a role in sperm ***,the mechanism of PHB-mediated regulation of sperm motility remai ns unk ***,we dem on strate for the first time that PHB interacts with protei n kinase B(AKT)and exists in a complex with phospho-PHB(pT258)and phospho-AKT in the mitochondrial sheath of murine sperm,as determined using colocalization and coimmunoprecipitation *** blocking AKT activity using wortmannin(a phosphatidylinositol 3-kinase[PI3K]inhibitor),murine sperm have significantly(P<0.05)decreased levels of phospho-PHB(pT258)and the total and progressive ***,significantly(P<0.05)lower levels of phospho-PI3K P85 subunit a+γ(pY199 and pY46)and phospho-AKT(pS473;pT308)are found in sperm from infertile asthenospermic and oligoasthenospermic men compared with no rmospermic subjects,which suggest a reduced activity of the PI3K/AKT pathway in these in fertile ***,these sperm from infertile subjects also have a significantly(P<0.05)lower level of phospho-PHB(pT258).Collectively,our findings suggest that the interaction of PHB with AKT in the mitochondrial sheath is critical for sperm motility,where PHB phosphorylation(pT258)level and PI3K/AKT activity are key regulatory factors.

关键词： male in fertility prohibitin(PHB) protein kinase B(AKT) sperm motility

来源：评论

学校读者我要写书评

暂无评论

Deep recursive embedding for high-dimensional data

arXiv

引用

arXiv 2021年

作者： Zhou, Zixia Wang, Yuanyuan Lelieveldt, Boudewijn P.F. Tao, Qian The Department of Electronic Engineering Fudan University Shanghai200433 China The Department of Electronic Engineering Fudan University Shanghai200433 China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200032 China The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands

t-distributed stochastic neighbor embedding (t-SNE) is a well-established visualization method for complex high-dimensional data. However, the original t-SNE method is nonparametric, stochastic, and often cannot well prevserve the global structure of data as it emphasizes local neighborhood. With t-SNE as a reference, we propose to combine the deep neural network (DNN) with the mathematical-grounded embedding rules for high-dimensional data embedding. We first introduce a deep embedding network (DEN) framework, which can learn a parametric mapping from high-dimensional space to low-dimensional embedding. DEN has a flexible architecture that can accommodate different input data (vector, image, or tensor) and loss functions. To improve the embedding performance, a recursive training strategy is proposed to make use of the latent representations extracted by DEN. Finally, we propose a two-stage loss function combining the advantages of two popular embedding methods, namely, t-SNE and uniform manifold approximation and projection (UMAP), for optimal visualization effect. We name the proposed method Deep Recursive Embedding (DRE), which optimizes DEN with a recursive training strategy and two-stage losse. Our experiments demonstrated the excellent performance of the proposed DRE method on high-dimensional data embedding, across a variety of public databases. Remarkably, our comparative results suggested that our proposed DRE could lead to improved global structure preservation. Copyright © 2021, The Authors. All rights reserved.

关键词： Clustering algorithms

来源：评论

学校读者我要写书评

暂无评论

Non-invasive Assessment of Hepatic Venous Pressure Gradient (HVPG) Based on MR Flow Imaging and Computational Fluid Dynamics

arXiv

引用

arXiv 2021年

作者： Wang, Kexin Wang, Shuo Xiong, Minghua Wang, Chengyan Wang, He Department of Physics Fudan University Shanghai China Digital Medical Research Center School of Basic Medical Sciences Fudan University Shanghai China Shanghai Key Laboratory of Medical Image Computing and Computer Assisted Intervention Shanghai China Shanghai Zhiyu Software Information Co. Ltd China Human Phenome Institute Fudan University Shanghai China Institute of Science and Technology for Brain-inspired Intelligence Fudan University Shanghai China Key Laboratory of Computational Neuroscience and Brain-Inspired Intelligence Fudan University Ministry of Education China

Clinically significant portal hypertension (CSPH) is a severe complication of chronic liver disease associated with cirrhosis, which is diagnosed by the measurement of hepatic venous pressure gradient (HVPG). However, HVPG measurement is invasive and therefore difficult to be widely applied in clinical routines. There is no currently available technique to measure HVPG noninvasively. Computational fluid dynamics (CFD) has been used for noninvasive measurement of vascular pressure gradient in the intracranial and coronary arteries. However, it has been scarcely employed in the hepatic vessel system due to the difficulties in reconstructing precise vascular anatomies and setting appropriate boundary conditions. Several computer tomography and ultrasound based studies have verified the effectiveness of virtual HVPG (vHVPG) by directly connecting the portal veins and hepatic veins before CFD simulations [16,12]. We apply the latest techniques of phase-contrast magnetic resonance imaging (PC-MRI) and DIXON to obtain the velocity and vessel anatomies at the same time. Besides, we improve the CFD pipeline in regards to the construction of vessel connections and reduction of calculation time. The proposed method shows high accuracy in the CSPH diagnosis in a study containing ten healthy volunteers and five patients. The MRI-based noninvasive HVPG measurement is promising in the clinical application of CSPH diagnosis. © 2021, CC BY.

关键词： Computational fluid dynamics

来源：评论

学校读者我要写书评

暂无评论

A Novel Method to Detect Multiple Arrhythmias Based on Time-Frequency Analysis and Convolutional Neural Networks

引用

IEEE ACCESS 2019年 7卷 170820-170830页

作者： Wu, Ziqian Lan, Tianjie Yang, Cuiwei Nie, Zhenning Department of Electronic Engineering Fudan University Shanghai 200433 China Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai Engineering Research Center of Assistive Devices Fudan University Shanghai 200093 China Department of Cardiology Shanghai Institute of Cardiovascular Diseases Zhongshan Hospital Fudan University Shanghai 200032 China

Electrocardiogram (ECG) is an efficient and commonly used tool for detecting arrhythmias. With the development of dynamic ECG monitoring, an effective and simple algorithm is needed to deal with large quantities of ECG data. In this study, we proposed a method to detect multiple arrhythmias based on time-frequency analysis and convolutional neural networks. For a short-time (10 s) single-lead ECG signal, the time-frequency distribution matrix of the signal was first obtained using a time-frequency transform method, and then a convolutional neural network was used to discriminate the rhythm of the signal. ECG data in multiple databases were used and were divided into 12 classes. Finally, the performance of three kinds of time-frequency transform methods are evaluated, including short-time Fourier transform (STFT), continuous wavelet transform (CWT), and pseudo Wigner-Ville distribution (PWVD). The best result was obtained by STFT, with an accuracy of 96.65%, an average sensitivity of 96.47%, an average specificity of 99.68%, and an average F-1 score of 96.27%, respectively. Especially, the area under curve (AUC) value is 0.9987. The proposed method in this work may be efficient and valuable to detect multiple arrhythmias for dynamic ECG monitoring.

关键词： Electrocardiography Time-frequency analysis Rhythm Databases Transforms Feature extraction Heart beat Arrhythmia detection convolutional neural networks ECG time-frequency analysis

来源：评论

学校读者我要写书评

暂无评论

WaveFuse: A unified unsupervised framework for image fusion with discrete wavelet transform

arXiv

引用

arXiv 2020年

作者： Liu, Shaolei Wang, Manning Song, Zhijian Digital Medical Research Center School of Basic Medical Science Fudan University China Shanghai Key Laboratory of Medical Image Computing and Computer Assited Intervention

We propose an unsupervised image fusion architecture for multiple application scenarios based on the combination of multi-scale discrete wavelet transform through regional energy and deep learning. To our best knowledge, this is the first time that a conventional frequency method has been combined with deep learning for feature maps fusion. The useful information of feature maps can be utilized adequately through multi-scale discrete wavelet transform in our proposed method. Compared with other state-of-the-art fusion methods, the proposed algorithm exhibits better fusion performance in both subjective and objective evaluation. Moreover, it's worth mentioning that comparable fusion performance trained in COCO dataset can be obtained by training with a much smaller dataset with only hundreds of images chosen randomly from COCO. Hence, the training time is shortened substantially, leading to the improvement of the model's performance both in practicality and training efficiency. Copyright © 2020, The Authors. All rights reserved.

关键词： image fusion

来源：评论

学校读者我要写书评

暂无评论

DPER: Diffusion Prior Driven Neural Representation for Limited Angle and Sparse View CT Reconstruction

arXiv

引用

arXiv 2024年

作者： Du, Chenhe Lin, Xiyue Wu, Qing Tian, Xuanyu Su, Ying Luo, Zhe Zheng, Rui Chen, Yang Wei, Hongjiang Zhou, S. Kevin Yu, Jingyi Zhang, Yuyao The School of Information Science and Technology ShanghaiTech University Shanghai China The Department of Critical Care Medicine Zhongshan Hospital Fudan University Shanghai China The Laboratory of Image Science and Technology The School of Computer Science and Engineering The Key Laboratory of New Generation Artificial Intelligence Technology and Its Interdisciplinary Applications Southeast University Ministry of Education Nanjing210096 China The School of Biomedical Engineering Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China School of Biomedical Engineering Suzhou Institute for Advanced Research University of Science and Technology of China Suzhou215123 China Institute of Computing Technology CAS Beijing100190 China

Limited-angle and sparse-view computed tomography (LACT and SVCT) are crucial for expanding the scope of X-ray CT applications. However, they face challenges due to incomplete data acquisition, resulting in diverse artifacts in the reconstructed CT images. Emerging implicit neural representation (INR) techniques, such as NeRF, NeAT, and NeRP, have shown promise in under-determined CT imaging reconstruction tasks. However, the unsupervised nature of INR architecture imposes limited constraints on the solution space, particularly for the highly ill-posed reconstruction task posed by LACT and ultra-SVCT. In this study, we introduce the Diffusion Prior Driven Neural Representation (DPER), an advanced unsupervised framework designed to address the exceptionally ill-posed CT reconstruction inverse problems. DPER adopts the Half Quadratic Splitting (HQS) algorithm to decompose the inverse problem into data fidelity and distribution prior sub-problems. The two sub-problems are respectively addressed by INR reconstruction scheme and pre-trained score-based diffusion model. This combination first injects the implicit image local consistency prior from INR. Additionally, it effectively augments the feasibility of the solution space for the inverse problem through the generative diffusion model, resulting in increased stability and precision in the solutions. We conduct comprehensive experiments to evaluate the performance of DPER on LACT and ultra-SVCT reconstruction with two public datasets (AAPM and LIDC), an in-house clinical COVID-19 dataset and a public raw projection dataset created by Mayo Clinic. The results show that our method outperforms the state-of-the-art reconstruction methods on in-domain datasets, while achieving significant performance improvements on out-of-domain (OOD) datasets. Copyright © 2024, The Authors. All rights reserved.

关键词： Inverse problems

来源：评论

学校读者我要写书评

暂无评论

Clomipramine inhibits microglial NLRP3 inflammasome in the hippocampus of depressive rats

Clomipramine inhibits microglial NLRP3 inflammasome in the h...

引用

中国解剖学会2021年年会

作者： Wang Yalin Zhang Shanshan Yue Na Liu Guixue Huang Huijie Han Qiuqin Gong Wenqing Chen Xiaorong Zhang Yaodong Yu Jin Xiao Honglei Qin Song Li Wensheng Liu Qiong Department of Integrative Medicine and Neurobiology School of Basic Medical Sciences Fudan University Department of Anatomy Histology and EmbryologySchool of Basic Medical SciencesFudan University Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Children's Hospital Affiliated to Zhengzhou University Henan Neural Development Engineering Research Center

Neuroinflammation is implicated in the pathophysiology of *** reduction of hippocampal volume in depression remains controversial because of interindividual variability in clinical ***,we studied the effects of clomipramine,a tricyclic antidepressant (TCA) that modulates serotonin and norepinephrine uptake,on chronic mild unpredictable stress (CMS)-induced depressive-like behaviors,hippocampal neuroinflammation, and hippocampal volume.

关键词： CMS Clomipramine inhibits microglial NLRP3 inflammasome in the hippocampus of depressive rats

来源：评论

学校读者我要写书评

暂无评论

DEEP RECURSIVE EMBEDDING FOR HIGH-DIMENSIONAL DATA

arXiv

引用

arXiv 2021年

作者： Zhou, Zixia Zu, Xinrui Wang, Yuanyuan Lelieveldt, Boudewijn P.F. Tao, Qian The Department of Electronic Engineering Fudan University Shanghai200433 China University of Twente Drienerlolaan 5 Enschede7522 NB Netherlands Key Laboratory of Medical Imaging Computing and Computer Assisted Intervention of Shanghai Shanghai200032 China The Division of Image Processing Department of Radiology Leiden University Medical Center Albinusdreef 2 Leiden2333 ZA Netherlands The Department of Imaging Physics Delft University of Technology Lorentzweg 1 Delft2628 CJ Netherlands

Embedding high-dimensional data onto a low-dimensional manifold is of both theoretical and practical value. In this paper, we propose to combine deep neural networks (DNN) with mathematics-guided embedding rules for high-dimensional data embedding. We introduce a generic deep embedding network (DEN) framework, which is able to learn a parametric mapping from high-dimensional space to low-dimensional space, guided by well-established objectives such as Kullback-Leibler (KL) divergence minimization. We further propose a recursive strategy, called deep recursive embedding (DRE), to make use of the latent data representations for boosted embedding performance. We exemplify the flexibility of DRE by different architectures and loss functions, and benchmarked our method against the two most popular embedding methods, namely, t-distributed stochastic neighbor embedding (t-SNE) and uniform manifold approximation and projection (UMAP). The proposed DRE method can map out-of-sample data and scale to extremely large datasets. Experiments on a range of public datasets demonstrated improved embedding performance in terms of local and global structure preservation, compared with other state-of-the-art embedding methods. © 2021, CC BY-NC-SA.

关键词： Deep neural networks

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：