检索结果-内蒙古大学图书馆

Mussel-inspired sulfated hyaluronan cryogel patch with antioxidant, anti-inflammatory, and drug-loading properties for multifunctional wound adhesives

引用

Bioactive Materials 2024年第10期40卷 582-596页

作者： Wonmoon Song Young Hwan Choi Young Gi Moon Changyub Lee M.Nivedhitha Sundaram Nathaniel S.Hwang School of Chemical and Biological Engineering Institute for Chemical ProcessesSeoul National UniversitySeoul08826Republic of Korea Interdisciplinary Program in Bioengineering Seoul National UniversitySeoul08826Republic of Korea Bio-MAX/N-Bio Institute Institute of BioEngineeringSeoul National UniversitySeoul08826Republic of Korea Division of Pediatric Cardiac Surgery Department of SurgeryJohns Hopkins School of MedicineBaltimoreMDUSA Institute of Engineering Research Seoul National UniversitySeoul08826Republic of Korea

Wounds, characterized by the disruption of the continuity of body tissues resulting from external trauma,manifest in diverse types and locations. Although numerous wound dressings are available for various woundscenarios, it remains challenging to find an integrative wound dressing capable of addressing diverse woundsituations. We focused on utilizing sulfated hyaluronan (sHA), known for its anti-inflammatory properties andcapacity to load cationic drugs. By conjugating catechol groups to sHA (sHA-CA), we achieved several advantagesin wound healing: 1) Fabrication of patches through crosslinking with catechol-modified high-molecularweighthyaluronan (HA(HMW)-CA), 2) Adhesiveness that enabled stable localization, 3) Radical scavenging thatcould synergize with the immunomodulation of sHA. The sHA-CA patches demonstrated therapeutic efficacy inthree distinct murine wound models: diabetic wound, hepatic hemorrhage, and post-surgical adhesion. Collectively,these findings underscore the potential of the sHA-CA patch as a promising candidate for the nextgenerationwound dressing.

关键词： Adhesive patch Anti-inflammation Sulfated hyaluronic acid Post-surgical adhesion Diabetic wound Hemostasis

来源：评论

学校读者我要写书评

暂无评论

PET image reconstruction using diffusion priors and half-quadratic splitting

PET image reconstruction using diffusion priors and half-qua...

引用

Medical Imaging 2025: Physics of Medical Imaging

作者： Bae, Sangjin Yu, Boxiao Lee, Jae Sung Gong, Kuang Interdisciplinary Program in Bioengineering Seoul National University Seoul08826 Korea Republic of J. Crayton Pruitt Family Department of Biomedical Engineering University of Florida GainesvilleFL32611 United States Department of Nuclear Medicine Seoul National University Hospital Seoul03080 Korea Republic of

ISBN: (纸本)9781510685888

PET image reconstruction is an inverse problem that aims to reconstruct the radiotracer distribution inside the body. This process involves finding an image x that maximizes the likelihood of the observed data y. To further improve image quality, maximum a posteriori (MAP) reconstruction is developed to exploit prior information about x, which requires designing a regularizer. Recent advances in diffusion models, a powerful class of generative models, have demonstrated their ability to effectively approximate data distributions. These models traditionally use ancestral sampling to generate images. As research on diffusion models progresses, it has been shown that they can also be used to design robust regularizers for inverse problems that go beyond ancestral sampling. In this work, we explored diffusion models-based regularizers for PET image reconstruction. Given the computational complexity of directly solving PET reconstruction with such regularizers, half-quadratic splitting (HQS) was utilized to decouple the regularizer from the original PET reconstruction objective. Our simulation study demonstrated that the proposed approach could generate high-quality reconstructions based solely on a limited number of iterations when compared to other reference methods. © 2025 SPIE.

关键词： Positron emission tomography

来源：评论

学校读者我要写书评

暂无评论

Score-based Diffusion Model based Synthetic CT Generation from MR Images and Post-hoc Uncertainty Analysis

Score-based Diffusion Model based Synthetic CT Generation fr...

引用

Medical Imaging 2025: Image Processing

作者： Yie, Si Young Yoon, Siyeop Yang, Jaewon Kim, Kyungsang Lee, Jae Sung Li, Quanzheng Interdisciplinary Program in Bioengineering Seoul National University Seoul03080 Korea Republic of Center for Advanced Medical Computing and Analysis Massachusetts General Hospital Havard Medical School BostonMA02114 United States Department of Radiology University of Texas Southwestern DallasTX75390 United States

ISBN: (纸本)9781510685901

PET/MRI and MR-guided radiotherapy have significantly advanced clinical diagnostics and treatment planning by integrating anatomy and function, while synthetic CT generation from MRI has emerged as a tool for extracting tissue density and attenuation properties. Despite these advances, generating synthetic CT from MRI remains challenging in the pelvic region due to substantial differences in tissue contrast and intensity between the two modalities. Traditional methods using dedicated MR sequences often fail to accurately represent bone structure. Recent deep learning models, including convolutional neural networks (CNNs) and generative adversarial networks (GANs), have improved the quality of synthetic CT generation, they typically lack uncertainty estimation, which limits their clinical utility. In this study, we propose a conditional diffusion model for generating pelvic CT from T1-weigted MR, enhanced by tissue segmentation extracted from TotalSegmentator-MR. We also investigated the self-explanatory characteristics of the diffusion model through uncertainty mapping from multiple realizations without requiring ground truth to enhance interpretability. Our results demonstrate that the diffusion model with tissue segmentation priors, produces higher-quality synthetic CTs and improved tissue differentiation compared to deterministic generative model and diffusion models conditioned only on MR data. Notably, the uncertainty map showed a strong spatial correlation with the ground truth-based error map. Furthermore, the inclusion of segmentation priors also reduces uncertainty, thereby improving the model's reliability. © 2025 SPIE.

关键词： Convolutional neural networks

来源：评论

学校读者我要写书评

暂无评论

Evaluation of a 3D Position Sensitive Time-of-flight PET Detector Unit with CPLD-based Frontend Electronics

Evaluation of a 3D Position Sensitive Time-of-flight PET Det...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Z. Zhao H.S. Shim C. Levin Radiology Department Stanford University Stanford California United States of America Seoul National University Interdisciplinary program of bioengineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

This study introduces and evaluates a stackable side-readout detector unit with second-generation frontend electronics for near 100 ps CTR Time-of-Flight 3D Position Sensitive (TOF-3DPS) detectors. This design utilizes a timing signal multiplexing scheme based on RF amplifiers and summing circuits to achieve 24:1 timing multiplexing and employs complex programmable logic devices (CPLDs) to facilitate high-precision energy measurement, and photon depth of interaction (DOI) positioning for single and multi-interaction inter-crystal scatter (ICS) events across different crystal elements within a detector unit. Experimental results with a single layer sub-unit comprising a $4 \times 2$ array of $3 \times 3 \times 10 \mathrm{~mm}^{3}$ LYSO:Ce crystals side-coupled with a $4 \times 6$ array of $3.16 \times 3.16 \mathrm{~mm}^{2}$ SiPMs yielded a 9.88 ± 0.86% energy resolution and a Coincidence Timing Resolution (CTR) of $121.28 \pm 3.35$ ps FWHM. Electrical collimation measurements performed at different positions along the 10 mm length of one crystal element produced a $1.44 \pm 0.44 \mathrm{~mm}$ FWHM DOI resolution. Additionally, electronic collimation of different columns in a detector unit revealed ICS event ratios for scatter to adjacent columns from the collimated column of 6.90%, 10.46%, 10.85%, and 5.33%, respectively. The side-readout detector layer sub-unit and the corresponding frontend circuitry have a footprint of only $27 \mathrm{~mm} \times 95 \mathrm{~mm}$, making it easy to stack and form a multi-layer TOF-3DPS block detector.

关键词： Multiplexing Temperature sensors Semiconductor device measurement Three-dimensional displays Semiconductor detectors Energy resolution Summing circuits

来源：评论

学校读者我要写书评

暂无评论

Single-photon emission from colloidal perovskite nanocrystals

引用

National Science Review 2025年第05期 10-14页

作者： Qingsen Zeng Shinyoung Hwang Hyeree Kim Tae-Woo Lee Department of Materials Science and Engineering Seoul National University Research Institute of Advanced Materials Seoul National University Interdisciplinary Program in Bioengineering Seoul National University SN Display Co.Ltd Institute of Engineering Research Soft Foundry Research Institute of Advanced Materials Seoul National University

A single-photon source (SPS) is a device that emits individual photons sequentially. SPSs are fundamental to the progress of quantum information technologies, in which photons convey quantum information. Photons have properties such as polarization, and spatial and temporal modes, which can be used to encode quantum information.

关键词：

来源：评论

学校读者我要写书评

暂无评论

SwiftMedSAM: An Ultra-lightweight Prompt-Based Universal Medical Image Segmentation Model for Highly Constrained Environments

SwiftMedSAM: An Ultra-lightweight Prompt-Based Universal Med...

引用

International Challenge on Segment Anything in Medical Images on Laptop held in conjunction with the IEEE/CVF Conference on Computer Vision and Pattern Recognition, CVPR 2024

作者： Kong, Youngbin Kim, Kwangtai Jeong, Seoi Lee, Kyu Eun Kong, Hyoun-Joong Interdisciplinary Program in Bioengineering Graduate School Seoul National University Seoul Korea Republic of Department of Transdisciplinary Medicine Seoul National University Hospital Seoul Korea Republic of Department of Surgery Seoul National University Hospital and College of Medicine Seoul Korea Republic of Department of Medicine Seoul National University College of Medicine Seoul Korea Republic of Innovative Medical Technology Research Institute Seoul National University Hospital Seoul Korea Republic of Interdisciplinary Program of Medical Informatics Seoul National University College of Medicine Seoul Korea Republic of

ISBN: (纸本)9783031818530

Medical image segmentation is a crucial step for accurate diagnosis and treatment planning, as it provides quantitative information about anatomical structures and pathological lesions in various clinical scenarios. However, the existing methodologies have limitations in terms of their generalizability and computational efficiency. In this study, we propose SwiftMedSAM, an ultra-lightweight prompt-based general model, to enable efficient medical image segmentation even in resource-constrained environments. Based on LiteMedSAM, we significantly reduced the model size and computational complexity through the hyperparameter optimization of the image encoder and mask decoder components. SwiftMedSAM showed remarkable performance across various imaging modalities enabling real-time inference in resource-limited computing environments. It achieved a validation score of 0.75 demonstrating that SwiftMedSAM outperformed the existing methodologies in terms of the trade-off between accuracy and efficiency. Owing to its unprecedented generalizability and low computational cost, SwiftMedSAM is expected to enable high-quality medical image analysis in resource-constrained settings, thereby contributing to advancements in precision medicine and telemedicine. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2025.

关键词： Medical imaging

来源：评论

学校读者我要写书评

暂无评论

Slit-Wall Differentiation Method for Depth-of-Interaction Measurement for PET

Slit-Wall Differentiation Method for Depth-of-Interaction Me...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： D. Lee H. Hemmati M. Yi S.I. Kwon University of California Davis Biomedical Engineering Davis California United States of America Seoul National University Interdisciplinary Program in Bioengineering College of Engineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In positron emission tomography (PET), accurately measuring the Depth-of-Interaction (DOI) of 511 keV gamma ray interactions is essential for improving spatial resolution in small animal PET, especially at off-center detector positions. DOI resolution can be improved by modifying crystal structures, reflectors, or by using dual readout techniques. Most methods, except for the more electronics-intensive dual side readout, increase light sharing among pixels, thereby reducing photon availability per pixel. This study introduces a novel Slit-Wall Differentiation (SWD) method, designed to restrict light sharing to just four adjacent pixels, thus enhancing DOI accuracy. The SWD method involves placing strategic slits on the adjacent faces of each pixel, controlling light sharing depending on the DOI position. DOI information is calculated from the output patterns of Silicon Photomultiplier (SiPM) arrays. The effectiveness of the proposed method was validated through GATE simulations (vGATE 9.2) using a $3 \times 3$ Lutetium-Yttrium Oxyorthosilicate (LYSO) array with enhanced specular reflectors (ESRs). An LYSO array fabricated based on the proposed configuration was successfully prepared. For practical validation, an experimental setup using a 4 $\times 4$ NUV-HD-MT (Broadcom) SiPM array is also configured.

关键词： Temperature measurement Photomultipliers Semiconductor device measurement Semiconductor detectors Position measurement Silicon Positron emission tomography

来源：评论

学校读者我要写书评

暂无评论

FPGA-Based Single-Input Time-to-Digital Converter with Rise Time Correction and Sub-2 ps Resolution for Precision Timing Applications

FPGA-Based Single-Input Time-to-Digital Converter with Rise ...

引用

IEEE Symposium on Nuclear Science (NSS/MIC)

作者： D. Lee M. Yi S.I. Kwon Biomedical Engineering University of California Davis Davis California United States of America Seoul National University Interdisciplinary Program in Bioengineering College of Engineering Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In numerous fields, including physics, industry, and medical technology, the precise measurement of extremely short time intervals, such as those below 100 ps, is essential. This research introduces an innovative FPGA-based time-to-digital converter (TDC) implemented on the UltraScale+ platform (VCU118, Xilinx). The UltraScale+ platform improves upon timing resolution by incorporating a CARRY8 primitive cell as a delay element, an improvement over the CARRY4, which was widely used in previous platforms. Through the novel end-of-propagation (EOP) technique, the implemented TDC achieves an average bin size of 1.11 ps, demonstrating significant resource efficiency compared to other reported FPGA-based TDCs. This study details the design, implementation, and empirical validation of the TDC. Additionally, a unique feature of the proposed TDC is its ability to measure the input pulse width and apply rise time correction without requiring additional inputs. To demonstrate its practical applicability, the developed TDC was connected to the output of an ultrafast Cherenkov-Radiator-Integrated (CRI)-MCP-PMT after evaluating its electrical performance. The preliminary coincidence timing resolution of a pair of CRI-MCP-PMTs shows improvements from 107 ps to 73 ps (FWHM) with the proposed rise time correction. These advancements highlight the potential of the TDC not only for next-generation medical applications but also for its transformative impact in applications demanding ultra-precise timing.

关键词： Industries Semiconductor device measurement Microwave integrated circuits Image resolution Semiconductor detectors Pulse measurements Medical services

来源：评论

学校读者我要写书评

暂无评论

RRED: A Radiology Report Error Detector based on Deep Learning Framework 4

RRED: A Radiology Report Error Detector based on Deep Learni...

引用

4th Workshop on Clinical Natural Language Processing, ClinicalNLP 2022

作者： Min, Dabin Kim, Kaeun Lee, Jong Hyuk Kim, Yisak Park, Chang Min Department of Radiology Seoul National University Hospital Korea Republic of Interdisciplinary Program in Bioengineering Seoul National University Graduate School Korea Republic of Department of Radiology Seoul National University College of Medicine Korea Republic of

ISBN: (纸本)9781955917773

Radiology report is an official record of radiologists’ interpretation of patients’ radiographs and it’s a crucial component in the overall medical diagnostic process. However, it can contain various types of errors that can lead to inadequate treatment or delay in diagnosis. To address this problem, we propose a deep learning framework to detect errors in radiology reports. Specifically, our method detects errors between findings and conclusion of chest X-ray reports based on a supervised learning framework. To compensate for the lack of data availability of radiology reports with errors, we develop an error generator to systematically create artificial errors in existing reports. In addition, we introduce a Medical Knowledge-enhancing Pre-training to further utilize the knowledge of abbreviations and key phrases frequently used in the medical domain. We believe that this is the first work to propose a deep learning framework for detecting errors in radiology reports based on a rich contextual and medical understanding. Validation on our radiologist-synthesized dataset, based on MIMIC-CXR, shows 0.80 and 0.95 of the area under precision-recall curve (AUPRC) and the area under the ROC curve (AUROC) respectively, indicating that our framework can effectively detect errors in the real-world radiology reports. © 2022 Association for Computational Linguistics.

关键词： Errors

来源：评论

学校读者我要写书评

暂无评论

Single-cell RNA-sequencing and subcellular spatial transcriptomics facilitate the translation of liver microphysiological systems for regulatory application

引用

Journal of Pharmaceutical Analysis 2023年第7期13卷 691-693页

作者： Dan Li Zhou Fang Qiang Shi Nicholas Zhang Binsheng Gong Weida Tong Ahmet F.Coskun Joshua Xu Division of Bioinformatics and Biostatistics National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Wallace H.Coulter Department of Biomedical Engineering Georgia Institute of Technology and Emory UniversityAtlantaGA30332USA Machine Learning Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Division of Systems Biology National Center for Toxicological ResearchU.S.Food and Drug AdministrationJeffersonAR72079USA Interdisciplinary Bioengineering Graduate Program Georgia Institute of TechnologyAtlantaGA30332USA Parker H.Petit Institute for Bioengineering and Bioscience Georgia Institute of TechnologyAtlantaGA30332USA

Reducing the use of animal models in drug development and safety assessment has long been supported by the *** and Drug Administration(FDA).The report by Royal Society for the Prevention of Cruelty to Animals indicates that in 2020,experiments involved the use of over 100 million animals,with the United States leading the list by utilizing 20 million *** ethical considerations associated with animal testing and the costs in terms of time and money,animal models are not always effective in predicting human reactions to drug *** animal testing has been the traditional method for assessing the safety and efficacy of drugs.

关键词： money utilizing testing

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：