ArXiv Pub Date : 2024-12-31

Zihan Pengmei, Chatipat Lorpaiboon, Spencer C Guo, Jonathan Weare, Aaron R Dinner

引用次数: 0

Augmenting Biomedical Named Entity Recognition with General-domain Resources. 利用通用领域资源增强生物医学命名实体识别。

ArXiv Pub Date : 2024-12-30

Yu Yin, Hyunjae Kim, Xiao Xiao, Chih Hsuan Wei, Jaewoo Kang, Zhiyong Lu, Hua Xu, Meng Fang, Qingyu Chen

{"title":"Augmenting Biomedical Named Entity Recognition with General-domain Resources.","authors":"Yu Yin, Hyunjae Kim, Xiao Xiao, Chih Hsuan Wei, Jaewoo Kang, Zhiyong Lu, Hua Xu, Meng Fang, Qingyu Chen","doi":"","DOIUrl":"","url":null,"abstract":"Training a neural network-based biomedical named entity recognition (BioNER) model usually requires extensive and costly human annotations. While several studies have employed multi-task learning with multiple BioNER datasets to reduce human effort, this approach does not consistently yield performance improvements and may introduce label ambiguity in different biomedical corpora. We aim to tackle those challenges through transfer learning from easily accessible resources with fewer concept overlaps with biomedical datasets. We proposed GERBERA, a simple-yet-effective method that utilized general-domain NER datasets for training. We performed multi-task learning to train a pre-trained biomedical language model with both the target BioNER dataset and the general-domain dataset. Subsequently, we fine-tuned the models specifically for the BioNER dataset. We systematically evaluated GERBERA on five datasets of eight entity types, collectively consisting of 81,410 instances. Despite using fewer biomedical resources, our models demonstrated superior performance compared to baseline models trained with additional BioNER datasets. Specifically, our models consistently outperformed the baseline models in six out of eight entity types, achieving an average improvement of 0.9% over the best baseline performance across eight entities. Our method was especially effective in amplifying performance on BioNER datasets characterized by limited data, with a 4.7% improvement in F1 scores on the JNLPBA-RNA dataset. This study introduces a new training method that leverages cost-effective general-domain NER datasets to augment BioNER models. This approach significantly improves BioNER model performance, making it a valuable asset for scenarios with scarce or costly biomedical datasets.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11468657/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142482885","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Contrast-Optimized Basis Functions for Self-Navigated Motion Correction in Quantitative MRI. 定量MRI中自我导航运动校正的对比优化基函数。

ArXiv Pub Date : 2024-12-27

Elisa Marchetto, Sebastian Flassbeck, Andrew Mao, Jakob Assländer

{"title":"Contrast-Optimized Basis Functions for Self-Navigated Motion Correction in Quantitative MRI.","authors":"Elisa Marchetto, Sebastian Flassbeck, Andrew Mao, Jakob Assländer","doi":"","DOIUrl":"","url":null,"abstract":"Purpose: The long scan times of quantitative MRI techniques make motion artifacts more likely. For MR-Fingerprinting-like approaches, this problem can be addressed with self-navigated retrospective motion correction based on reconstructions in a singular value decomposition (SVD) subspace. However, the SVD promotes high signal intensity in all tissues, which limits the contrast between tissue types and ultimately reduces the accuracy of registration. The purpose of this paper is to rotate the subspace for maximum contrast between two types of tissue and improve the accuracy of motion estimates.Methods: A subspace is derived that promotes contrasts between brain parenchyma and CSF, achieved through the generalized eigendecomposition of mean autocorrelation matrices, followed by a Gram-Schmidt process to maintain orthogonality.We tested our motion correction method on 85 scans with varying motion levels, acquired with a 3D hybrid-state sequence optimized for quantitative magnetization transfer imaging.Results: A comparative analysis shows that the contrast-optimized basis significantly improve the parenchyma-CSF contrast, leading to smoother motion estimates and reduced artifacts in the quantitative maps.Conclusion: The proposed contrast-optimized subspace improves the accuracy of the motion estimation.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703326/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980010","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

RTify: Aligning Deep Neural Networks with Human Behavioral Decisions. RTify：将深度神经网络与人类行为决策相结合。

ArXiv Pub Date : 2024-12-26

Yu-Ang Cheng, Ivan Felipe Rodriguez, Sixuan Chen, Kohitij Kar, Takeo Watanabe, Thomas Serre

{"title":"RTify: Aligning Deep Neural Networks with Human Behavioral Decisions.","authors":"Yu-Ang Cheng, Ivan Felipe Rodriguez, Sixuan Chen, Kohitij Kar, Takeo Watanabe, Thomas Serre","doi":"","DOIUrl":"","url":null,"abstract":"Current neural network models of primate vision focus on replicating overall levels of behavioral accuracy, often neglecting perceptual decisions' rich, dynamic nature. Here, we introduce a novel computational framework to model the dynamics of human behavioral choices by learning to align the temporal dynamics of a recurrent neural network (RNN) to human reaction times (RTs). We describe an approximation that allows us to constrain the number of time steps an RNN takes to solve a task with human RTs. The approach is extensively evaluated against various psychophysics experiments. We also show that the approximation can be used to optimize an \"ideal-observer\" RNN model to achieve an optimal tradeoff between speed and accuracy without human data. The resulting model is found to account well for human RT data. Finally, we use the approximation to train a deep learning implementation of the popular Wong-Wang decision-making model. The model is integrated with a convolutional neural network (CNN) model of visual processing and evaluated using both artificial and natural image stimuli. Overall, we present a novel framework that helps align current vision models with human behavior, bringing us closer to an integrated model of human vision.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703321/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985851","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optical detection of the spatial structural alteration in the human brain tissues/cells and DNA/chromatin due to Parkinson's disease. 帕金森病引起的人脑组织/细胞和DNA/染色质空间结构改变的光学检测

ArXiv Pub Date : 2024-12-25

Fatemah Alharthi, Dhruvil Solanki, Ishmael Apachigawo, Jianfeng Xiao, Mohammad Moshahid Khan, Prabhakar Pradhan

{"title":"Optical detection of the spatial structural alteration in the human brain tissues/cells and DNA/chromatin due to Parkinson's disease.","authors":"Fatemah Alharthi, Dhruvil Solanki, Ishmael Apachigawo, Jianfeng Xiao, Mohammad Moshahid Khan, Prabhakar Pradhan","doi":"","DOIUrl":"","url":null,"abstract":"Parkinson's disease (PD) is considered one of the most frequent neurological diseases in the world. There is a need to study the early and efficient biomarkers of Parkinson's, such as changes in structural disorders like DNA/chromatin, especially at the subcellular level in the human brain. We used two techniques, Partial wave spectroscopy (PWS) and Inverse Participation Ratio (IPR), to detect the changes in structural disorder in the human brain tissue samples. It was observed from the PWS experiment that there was an increase in structural disorder in Parkinson's disease tissues/cells when compared to normal tissues/cells using mesoscopic light transport theory. Furthermore, the IPR experiment also showed DNA/chromatin structural alterations that have the same trend and support the PWS results. The increase in mass density in the nuclei components, such as DNA/chromatin, can be linked to the aggregation of alpha-synuclein in the substantia nigra of the brain. This protein deposition is considered a significant cause of neuronal death in the brains of PD patients. We also did a histological analysis of brain tissues, which supports our results from dual photonics techniques. The results show that this dual technique is a powerful approach to detect the changes. Our results highlight the potential of the parameter, related to the structural disorder strength, as an efficient biomarker for PD progress, paving the way for research into early disease detection.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-25","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703318/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980386","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

An AI-directed analytical study on the optical transmission microscopic images of Pseudomonas aeruginosa in planktonic and biofilm states. 浮游和生物膜状态铜绿假单胞菌光学透射显微图像的人工智能定向分析研究。

ArXiv Pub Date : 2024-12-24

Bidisha Sengupta, Mousa Alrubayan, Yibin Wang, Esther Mallet, Angel Torres, Ravyn Solis, Haifeng Wang, Prabhakar Pradhan

引用次数: 0

Agreement of Image Quality Metrics with Radiological Evaluation in the Presence of Motion Artifacts. 运动伪影存在下图像质量度量与放射学评价的一致性。

ArXiv Pub Date : 2024-12-24

Elisa Marchetto, Hannah Eichhorn, Daniel Gallichan, Julia A Schnabel, Melanie Ganz

{"title":"Agreement of Image Quality Metrics with Radiological Evaluation in the Presence of Motion Artifacts.","authors":"Elisa Marchetto, Hannah Eichhorn, Daniel Gallichan, Julia A Schnabel, Melanie Ganz","doi":"","DOIUrl":"","url":null,"abstract":"Purpose: Reliable image quality assessment is crucial for evaluating new motion correction methods for magnetic resonance imaging. In this work, we compare the performance of commonly used reference-based and reference-free image quality metrics on a unique dataset with real motion artifacts. We further analyze the image quality metrics' robustness to typical pre-processing techniques.Methods: We compared five reference-based and five reference-free image quality metrics on data acquired with and without intentional motion (2D and 3D sequences). The metrics were recalculated seven times with varying pre-processing steps. The anonymized images were rated by radiologists and radiographers on a 1-5 Likert scale. Spearman correlation coefficients were computed to assess the relationship between image quality metrics and observer scores.Results: All reference-based image quality metrics showed strong correlation with observer assessments, with minor performance variations across sequences. Among reference-free metrics, Average Edge Strength offers the most promising results, as it consistently displayed stronger correlations across all sequences compared to the other reference-free metrics. Overall, the strongest correlation was achieved with percentile normalization and restricting the metric values to the skull-stripped brain region. In contrast, correlations were weaker when not applying any brain mask and using min-max or no normalization.Conclusion: Reference-based metrics reliably correlate with radiological evaluation across different sequences and datasets. Pre-processing steps, particularly normalization and brain masking, significantly influence the correlation values. Future research should focus on refining pre-processing techniques and exploring machine learning approaches for automated image quality evaluation.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703327/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142985846","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Optimizing In Vivo Data Acquisition for Robust Clinical Microvascular Imaging Using Ultrasound Localization Microscopy. 利用超声定位显微镜优化临床微血管成像的体内数据采集。

ArXiv Pub Date : 2024-12-24

Chengwu Huang, U-Wai Lok, Jingke Zhang, Xiang Yang Zhu, James D Krier, Amy Stern, Kate M Knoll, Kendra E Petersen, Kathryn A Robinson, Gina K Hesley, Andrew J Bentall, Thomas D Atwell, Andrew D Rule, Lilach O Lerman, Shigao Chen

{"title":"Optimizing In Vivo Data Acquisition for Robust Clinical Microvascular Imaging Using Ultrasound Localization Microscopy.","authors":"Chengwu Huang, U-Wai Lok, Jingke Zhang, Xiang Yang Zhu, James D Krier, Amy Stern, Kate M Knoll, Kendra E Petersen, Kathryn A Robinson, Gina K Hesley, Andrew J Bentall, Thomas D Atwell, Andrew D Rule, Lilach O Lerman, Shigao Chen","doi":"","DOIUrl":"","url":null,"abstract":"Ultrasound localization microscopy (ULM) enables microvascular imaging at spatial resolutions beyond the acoustic diffraction limit, offering significant clinical potentials. However, ULM performance relies heavily on microbubble (MB) signal sparsity, the number of detected MBs, and signal-to-noise ratio (SNR), all of which vary in clinical scenarios involving bolus MB injections. These sources of variations underscore the need to optimize MB dosage, data acquisition timing, and imaging settings in order to standardize and optimize ULM of microvasculature. This pilot study investigated temporal changes in MB signals during bolus injections in both pig and human models to optimize data acquisition for clinical ULM. Quantitative indices were developed to evaluate MB signal quality, guiding selection of acquisition timing that balances the MB localization quality and adequate MB counts. The effects of transmitted voltage and dosage were also explored. In the pig model, a relatively short window (approximately 10 seconds) for optimal acquisition was identified during the rapid wash-out phase, highlighting the need for real-time MB signal monitoring during data acquisition. The slower wash-out phase in humans allowed for a more flexible imaging window of 1-2 minutes, while trade-offs were observed between localization quality and MB density (or acquisition length) at different wash-out phase timings. Guided by these findings, robust ULM imaging was achieved in both pig and human kidneys using a short period of data acquisition, demonstrating its feasibility in clinical practice. This study provides insights into optimizing data acquisition for consistent and reproducible ULM, paving the way for its standardization and broader clinical applications.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11703319/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"142980550","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

Comprehensive Optimization of Interferometric Diffusing Wave Spectroscopy (iDWS). 干涉散射波光谱（iDWS）的综合优化。

ArXiv Pub Date : 2024-12-23

Mingjun Zhao, Leah Dickstein, Akshay S Nadig, Wenjun Zhou, Santosh Aparanji, Hector Garcia Estrada, Shing-Jiuan Liu, Ting Zhou, Weijian Yang, Aaron Lord, Vivek J Srinivasan

引用次数: 0

Diverging network architecture of the C. elegans connectome and signaling network. 秀丽隐杆线虫连接体和信号网络的分化网络结构。

ArXiv Pub Date : 2024-12-19

Sophie Dvali, Caio Seguin, Richard Betzel, Andrew M Leifer

{"title":"Diverging network architecture of the C. elegans connectome and signaling network.","authors":"Sophie Dvali, Caio Seguin, Richard Betzel, Andrew M Leifer","doi":"","DOIUrl":"","url":null,"abstract":"The connectome describes the complete set of synaptic contacts through which neurons communicate. While the architecture of the C. elegans connectome has been extensively characterized, much less is known about the organization of causal signaling networks arising from functional interactions between neurons. Understanding how effective communication pathways relate to or diverge from the underlying structure is a central question in neuroscience. Here, we analyze the modular architecture of the C. elegans signal propagation network, measured via calcium imaging and optogenetics, and compare it to the underlying anatomical wiring measured by electron microscopy. Compared to the connectome, we find that signaling modules are not aligned with the modular boundaries of the anatomical network, highlighting an instance where function deviates from structure. An exception to this is the pharynx which is delineated into a separate community in both anatomy and signaling. We analyze the cellular compositions of the signaling architecture and find that its modules are enriched for specific cell types and functions, suggesting that the network modules are neurobiologically relevant. Lastly, we identify a \"rich club\" of hub neurons in the signaling network. The membership of the signaling rich club differs from the rich club detected in the anatomical network, challenging the view that structural hubs occupy positions of influence in functional (signaling) networks. Our results provide new insight into the interplay between brain structure, in the form of a complete synaptic-level connectome, and brain function, in the form of a system-wide causal signal propagation atlas.","PeriodicalId":93888,"journal":{"name":"ArXiv","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2024-12-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11702810/pdf/","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"143017911","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"OA","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 0

ArXiv最新文献