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arXiv 2025年

作者： Jo, Sanghyun Lee, Ziseok Lee, Wooyeol Kim, Kyungsu OGQ Seoul Korea Republic of Department of Biomedical Sciences Seoul National University Seoul Korea Republic of Department of Computer Science and Engineering Seoul National University Seoul Korea Republic of School of Transdisciplinary Innovations Interdisciplinary Program in Artificial Intelligence Seoul National University Seoul Korea Republic of

Achieving precise panoptic segmentation heavily relies on pixel-wise instance annotations, but obtaining such datasets is costly. Unsupervised instance segmentation (UIS) eliminates annotation requirements but struggles with adjacent instance merging and single-instance fragmentation, largely due to the limitations of DINO-based backbones, which lack strong instance separation cues. Weakly-supervised panoptic segmentation (WPS) reduces annotation costs by using sparse labels (e.g., points, boxes), yet these annotations remain expensive and introduce human bias and boundary errors, limiting performance. To address these challenges, we propose DiffEGG (Diffusion-Driven EdGe Generation), a fully annotation-free method that extracts instance-aware features from pretrained diffusion models to generate precise instance edge maps. DiffEGG fundamentally differs from prior UIS and WPS approaches by leveraging pretrained diffusion models as a backbone. Unlike DINO-based UIS methods, diffusion models inherently capture fine-grained, instance-aware features, enabling more precise boundary delineation. DiffEGG further enhances edge connectivity through self-supervised fine-tuning, progressively improving instance separation. For WPS, DiffEGG completely eliminates annotation costs and human bias by operating without any form of manual supervision, addressing the key limitations of prior best methods. Additionally, we introduce RIP, a post-processing technique that fuses DiffEGG’s edge maps with segmentation masks in a task-agnostic manner. This broad applicability allows DiffEGG to be seamlessly integrated into various segmentation frameworks. When applied to UIS, DiffEGG and RIP achieve an average +4.4 AP improvement over prior best UIS methods. When combined with weakly-supervised semantic segmentation (WSS), DiffEGG enables WPS without instance annotations, outperforming prior best point-supervised WPS methods by +1.7 PQ. These results demonstrate that DiffEGG’s edge maps serv

关键词： Semantic Segmentation

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Printability and cytotoxicity of alginate/agarose hydrogel with carboxylmethyl cellulose and apple powder

Printability and cytotoxicity of alginate/agarose hydrogel w...

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biomedical engineering International Conference (BMEiCON)

作者： K. Chessadangkul N. Damrongplasit S. Morakul T. Tharasanit A. Pimpin Biomedical engineering program Faculty of Engineering Chulalongkorn University Bangkok Thailand Department of Obstetrics Gynaecology and Reproduction Faculty of Veterinary Science Chulalongkorn University Bangkok Thailand Department of Mechanical engineering Faculty of Engineering Chulalongkorn University Bangkok Thailand

ISBN: (纸本)9781665489041

The cultured meat is the solution to reduce resources using in a traditional meat production. It helps produce meat without killing livestock and decrease residue products. The method could also integrate with scaffold’s material which does not derive from animal products. This study aims to investigate the effects of carboxymethyl cellulose (CMC) and apple powder on printability and cytotoxicity as additives in alginate/agarose-based hydrogel. 3D structures of them were printed to find a proper printing condition. From our experiments, the structure could maintain their shapes and uniform line sizes for carboxylmethyl cellulose, but not for apple powder at the 2% w/v alginate and 0.8% w/v agarose. However, the combination of them could be printed well. In parallel, 293FT cells were cultured with hydrogel drop to test cytotoxicity. It showed that the hydrogel with both additives does not harm cells during 8-day culturing.

关键词： Viscosity Printing Powders Additives Toxicology Three-dimensional displays Shape

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Differential Responses of Transplanted Stem Cells to Diseased Environment Unveiled by a Molecular NIR-II Cell Tracker

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Research 2021年第1期2021卷 935-950页

作者： Hao Chen Huaxiao Yang Chen Zhang Si Chen Xin Zhao Mark Zhu Zhiming Wang Yuebing Wang Hung-Ta Wo Kai Li Zhen Cheng Center for Molecular Imaging Research Shanghai Institute of Materia MedicaChinese Academy of SciencesShanghai 201203China Molecular Imaging Program at Stanford(MIPS) Bio-X Programand Department of RadiologyCanary Center at Stanford for Cancer Early DetectionStanford UniversityStanfordCA 94305-5344USA University of North Texas Biomedical EngineeringDentonTX 76207USA Department of Biomedical Engineering Southern University of Science and TechnologyShenzhenGuangdong 518055China Department of Neurology Xiangya HospitalCentral South UniversityXiangya Road 88ChangshaHunan 410008China Stanford Cardiovascular Institute StanfordCA 94305USA Division of Cardiology Department of Internal MedicineChang Gung Memorial HospitalLinkouTaiwan33305China

Stem cell therapy holds high promises in regenerative *** major challenge of clinical translation is to precisely and quantitatively evaluate the in vivo cell distribution,migration,and engraftment,which cannot be easily achieved by current *** address this issue,for the first time,we have developed a molecular cell tracker with a strong fluorescence signal in the second near-infrared(NIR-II)window(1,000-1,700 nm)for real-time monitoring of in vivo cell behaviors in both healthy and diseased animal *** NIR-II tracker(CelTrac1000)has shown complete cell labeling with low cytotoxicity and profound long-term tracking ability for 30 days in high spatiotemporal resolution for semiquantification of the biodistribution of transplanted stem *** advantage of the unique merits of CelTrac1000,the responses of transplanted stem cells to different diseased environments have been discriminated and ***,we also demonstrate CelTrac1000 as a universal and effective technique for ultrafast real-time tracking of the cellular migration and distribution in a 100μm single-cell cluster spatial resolution,along with the lung contraction and heart *** such,this NIR-II tracker will shift the optical cell tracking into a single-cell cluster and millisecond temporal resolution for better evaluating and understanding stem cell therapy,affording optimal doses and efficacy.

关键词： doses distribution holds

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Centrifugal Spinning of Porous Polylactic Acid Fibers by Centrifugal Spinning with Phase Separation for Oil Removal Application

SSRN

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SSRN 2024年

作者： Negoro, Masaki Doan, Hoan Ngoc Vo, Phu Phong Khuat, Khanh Van Thi Kinashi, Kenji Sakai, Wataru Tsutsumi, Naoto Master’s Program of Innovative Materials Kyoto Institute of Technology Matsugasaki Sakyo Kyoto606-8585 Japan Tissue Engineering and Regenerative Medicine Laboratory School of Biomedical Engineering International University Vietnam National University Ho Chi Minh City Viet Nam Faculty of Chemistry University of Science Ho Chi Minh City Viet Nam Doctor’s Program of Materials Chemistry Graduate School of Science and Technology Kyoto Institute of Technology Matsugasaki Sakyo Kyoto606-8585 Japan Faculty of Materials Science and Engineering Kyoto Institute of Technology Matsugasaki Sakyo Kyoto606-8585 Japan

Developing biodegradable oil absorption fibrous materials is essential because discarding conventional separation materials could cause secondary pollution due to their nondegradable properties. In this study, highly hydrophobic and superoleophilic porous polylactic acid (PLA) fibers were prepared using centrifugal spinning combined with nonsolvent-induced phase separation. The porous structure of PLA fibers was controlled by the ratio between good solvent and nonsolvent in the spinning solutions. The morphology and physical properties of the obtained PLA fibers were investigated using various measurement techniques. The PLA fibrous membrane prepared from a PLA solution containing chloroform/dimethylformamide (80/20 w/w) indicated not only a high water contact angle but also a high oil sorption value. The porous PLA fibers are a potential candidate for use as green materials for environmental applications. © 2024, The Authors. All rights reserved.

关键词： Spinning (fibers)

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Oscillation quenching in Stuart-Landau oscillators via dissimilar repulsive coupling

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Physical Review Research 2023年第1期5卷 013074-013074页

作者： Subhasanket Dutta Omar Alamoudi Yash Shashank Vakilna Sandipan Pati Sarika Jalan Complex Systems Lab Department of Physics Indian Institute of Technology Indore Khandwa Road Simrol Indore-453552 India Texas Institute for Restorative Neurotechnologies The University of Texas Health Science Center at Houston Houston Texas 77225 USA Biomedical Engineering Program King Abdulaziz University Jeddah Saudi Arabia Department of Biosciences and Biomedical Engineering Indian Institute of Technology Indore Khandwa Road Simrol Indore-453552 India

Quenching of oscillations, namely, amplitude and oscillations death, is an emerging phenomenon exhibited by many real-world complex systems. Here, we introduce a scheme that combines dissimilar couplings and repulsive feedback links for the interactions of Stuart-Landau oscillators and analytically derive the conditions required for the amplitude death. Importantly, this analysis is independent of the network size, presents a generalized approach to calculate the stability conditions for various different coupling schemes, and befits nonidentical oscillators as well. Last, we discuss the similarities of the quenching of oscillations phenomenon with the postictal generalized Electroencephalogram (EEG) suppression in convulsive seizures.

关键词： Bifurcations Coupled oscillators Neuronal dynamics Neuronal network activity

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Amelioration of the brain structural connectivity is accompanied with changes of gut microbiota in a tuberous sclerosis complex mouse model

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Translational Psychiatry 2024年第1期14卷 68页

作者： Hsieh, Christine Chin-jung Lo, Yu-Chun Wang, Hsin-Hui Shen, Hsin-Ying Chen, You-Yin Lee, Yi-Chao Biomedical Translation Research Center Academia Sinica Taipei Taiwan Ph.D. Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan Neuroscience Research Center Taipei Medical University Taipei Taiwan Department of Biomedical Engineering National Yang Ming Chiao Tung University Taipei Taiwan International Master Program in Medical Neuroscience College of Medical Science and Technology Taipei Medical University Taipei Taiwan

Tuberous sclerosis complex (TSC) is a genetic disease that causes benign tumors and dysfunctions in many organs, including the brain. Aside from the brain malformations, many individuals with TSC exhibit neuropsychiatric symptoms. Among these symptoms, autism spectrum disorder (ASD) is one of the most common co-morbidities, affecting up to 60% of the population. Past neuroimaging studies strongly suggested that the impairments in brain connectivity contribute to ASD, whether or not TSC-related. Specifically, the tract-based diffusion tensor imaging (DTI) analysis provides information on the fiber integrity and has been used to study the neuropathological changes in the white matter of TSC patients with ASD symptoms. In our previous study, curcumin, a diet-derived mTOR inhibitor has been shown to effectively mitigate learning and memory deficits and anxiety-like behavior in Tsc2 ^+/− mice via inhibiting astroglial proliferation. Recently, gut microbiota, which is greatly influenced by the diet, has been considered to play an important role in regulating several components of the central nervous system, including glial functions. In this study, we showed that the abnormal social behavior in the Tsc2 ^+/− mice can be ameliorated by the dietary curcumin treatment. Second, using tract-based DTI analysis, we found that the Tsc2 ^+/− mice exhibited altered fractional anisotropy, axial and radial diffusivities of axonal bundles connecting the prefrontal cortex, nucleus accumbens, hypothalamus, and amygdala, indicating a decreased brain network. Third, the dietary curcumin treatment improved the DTI metrics, in accordance with changes in the gut microbiota composition. At the bacterial phylum level, we showed that the abundances of Actinobacteria, Verrucomicrobia, and Tenericutes were significantly correlated with the DTI metrics FA, AD, and RD, respectively. Finally, we revealed that the expression of myelin-associated proteins, myelin bassic p

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Pulmonary Disease Pattern Recognition on X-Ray Radiography Image Using Artificial Neural Network (ANN) Method 3

Pulmonary Disease Pattern Recognition on X-Ray Radiography I...

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3rd Annual Scientific Meeting on Medical Physics and Biophysics, PIT-FMB in conjunction with the 17th South-East Asia Congress of Medical Physics, SEACOMP 2019

作者： Fitriyah, N. Kurniawati, L.D. Purwanti, E. Astuti, S.D. Department of Physics Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Biomedical Engineering Study Program Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia Department of Biomedical Engineering Post-Graduate Program Faculty of Science and Technology Universitas Airlangga Surabaya60115 Indonesia

This research aims to recognize the pattern of pulmonary disease on x-ray radiography image using artificial neural network (ANN) method. The images, which were used such as images of healthy pulmonary, pulmonary tuberculosis, and pulmonary tumour. Pattern recognition was using an extraction feature of GLCM (Gray Level Co-occurrence Matrix) and back propagation method. Before being identified, the images were processed by median filter and adaptive histogram equalization. The GLCM features that used were homogeneity, energy, contrast, variance and correlation. The parameters were learning rate and hidden layer. Learning rate was 0.3 and hidden layer was 25. Back propagation training showed 100% accuracy, which all of 44 images were used had been successfully identified. From the result, the healthy pulmonary showed 60% accuracy, 83.3% for pulmonary tuberculosis and 100% for pulmonary tumor. Hence, the overall result showed 81.25% accuracy, which 13 of 16 images had been successfully identified. From these result, extraction feature of GLCM using back propagation method was capable to recognize the pattern of pulmonary disease. However, due to narrow range of the feature, this application may not be used optimally for comparing features in every category of images. Therefore, the further research is needed to determine the best features and parameters of training back propagation. © Published under licence by IOP Publishing Ltd.

关键词： Pattern recognition

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A Comparative Study of Machine Learning Classifiers for Enhancing Knee Osteoarthritis Diagnosis

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Information (Switzerland) 2024年第4期15卷 183页

作者： Raza, Aquib Phan, Thien-Luan Li, Hung-Chung Hieu, Nguyen Van Nghia, Tran Trung Ching, Congo Tak Shing Graduate Institute of Biomedical Engineering National Chung Hsing University Taichung402 Taiwan Department of Physics and Electronic Engineering University of Science Vietnam National University of Ho Chi Minh City Ho Chi Minh City70000 Viet Nam Undergraduate Program of Intellectual Creativity Engineering National Chung Hsing University Taichung402 Taiwan VNU-HCM Ho Chi Minh City72409 Viet Nam Department of Electrical Engineering National Chi Nan University Puli Township545 Taiwan International Doctoral Program in Agriculture National Chung Hsing University Taichung402 Taiwan

Knee osteoarthritis (KOA) is a leading cause of disability, particularly affecting older adults due to the deterioration of articular cartilage within the knee joint. This condition is characterized by pain, stiffness, and impaired movement, posing a significant challenge in medical diagnostics and treatment planning, especially due to the current inability for early and accurate detection or monitoring of disease progression. This research introduces a multifaceted approach employing feature extraction and machine learning (ML) to improve the accuracy of diagnosing and classifying KOA stages from radiographic images. Utilizing a dataset of 3154 knee X-ray images, this study implemented feature extraction methods such as Histogram of Oriented Gradients (HOG) with Linear Discriminant Analysis (LDA) and Min–Max scaling to prepare the data for classification. The study evaluates six ML classifiers—K Nearest Neighbors classifier, Support Vector Machine (SVM), Gaussian Naive Bayes, Decision Tree, Random Forest, and XGBoost—optimized via GridSearchCV for hyperparameter tuning within a 10-fold Stratified K-Fold cross-validation framework. An ensemble model has also been made for the already high-accuracy models to explore the possibility of enhancing the accuracy and reducing the risk of overfitting. The XGBoost classifier and the ensemble model emerged as the most efficient for multiclass classification, with an accuracy of 98.90%, distinguishing between healthy and unhealthy knees. These results underscore the potential of integrating advanced ML methodologies for the nuanced and accurate diagnosis and classification of KOA, offering new avenues for clinical application and future research in medical imaging diagnostics. © 2024 by the authors.

关键词： Extraction

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Flexible and Wearable PEDOT-Paper Pressure Sensor for Detecting Human Voice

Flexible and Wearable PEDOT-Paper Pressure Sensor for Detect...

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International Conference on Big Data and Smart Computing (BIGCOMP)

作者： Busra Ozlu Bong Sup Shim Inha University South Korea Program in Biomedical Science and Engineering Inha University South Korea

ISBN: (数字)9781728189246

ISBN: (纸本)9781728189253

Flexible pressure sensors are gaining considerable attention as wearable devices to be potentially utilized in human-machine interfaces. However, the preparation of pressure sensors through a simple, environmentally friendly, and cost-efficient fabrication process, remains as a challenge. In this study, we developed a flexible and wearable piezoresistive pressure sensor which consists of a polyethylene terephthalate (PET) as a flexible substrate for printing silver interdigitated electrodes and a poly(3,4-ethylenedioxythiophene) polystyrene sulfonate (PEDOT:PSS) coated tissue paper as an active material. The PEDOT-Paper pressure sensor showed a sensitivity of 1.7/kPa in the range of 0 to 0.46 kPa, a response time of 240 ms and a recovery time of 306 ms. The potential application of this sensor for human voice detection was also demonstrated by mounting the sensor on the throat of a volunteer and pronouncing the words, “Hello” and “Inha University”. The good repeatability and characteristic curves were achieved for each word, confirming the promising application of the PEDOT-Paper pressure sensor in the field of voice recognition.

关键词： Pressure sensors Electric potential Sensitivity Wearable computers Speech recognition Time factors Character recognition

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Performance Evaluation of Cs3Cu2I5 Perovskite Scintillator Grown by Seedless SEST Method

Performance Evaluation of Cs3Cu2I5 Perovskite Scintillator G...

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IEEE Symposium on Nuclear science (NSS/MIC)

作者： S. Song J. Seo M. Park J.-Y. Yeom Department of Bioengineering Korea University Seoul Republic of Korea Interdisciplinary Program in Precision Public Health Korea University Seoul Republic of Korea Department of Health and Safety Convergence Science Korea University Seoul Republic of Korea School of Biomedical Engineering Korea University Seoul Republic of Korea

ISBN: (数字)9798350388152

ISBN: (纸本)9798350388169

In this study, we utilized the seedless Slow evaporation solution growth technique (SEST) method to grow Cs 3 Cu 2 I 5 , a 0-D perovskite scintillator material, at room temperature. The growth was conducted under conditions of 23°C temperature and 40% humidity for 10 days, resulting in obtaining multiple crystals of 5 mm in size. Using single crystal Cs 3 Cu 2 I 5 detectors grown in our lab, we evaluated its performance using radioactive isotopes ${ }^{137} \mathrm{Cs},{ }^{241} \mathrm{Am},{ }^{54} \mathrm{Mn},{ }^{60} \mathrm{Co},{ }^{22} \mathrm{Na}$, and ${}^{57}\mathrm{Co}$, and acquired energy resolutions of 8.55%, 23.35%, 7.59%, 6.49%, 9.38%, and 16.8%, respectively. In comparison with polycrystalline counterparts, single crystal Cs 3 Cu 2 I 5 exhibited superior performance, although both demonstrated excellent characteristics. By comparison, measurement using GAGG:Ce as a reference scintillator with the same setup showed an energy resolution of 10.00 %.

关键词： Temperature measurement Performance evaluation Semiconductor device measurement Microwave integrated circuits Scintillators Temperature Semiconductor detectors

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