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Quasi-static ultrasound elastography of ex-vivo porcine vocal folds during passive elongation and adduction

Journal of Voice 2025年第3期39卷 635-646页

作者： Lamprecht, Raphael Scheible, Florian Veltrup, Reinhard Schaan, Casey Semmler, Marion Henningson, Jann-Ole Sutor, Alexander Institute of Measurement and Sensor Technology UMIT TIROL – Private University for Health Sciences and Health Technology Hall in Tirol Austria Division of Phoniatrics and Pediatric Audiology Department of Otorhinolaryngology Head- and Neck surgery University Hospital Erlangen Friedrich-Alexander-University Erlangen-Nürnberg Erlangen Germany Chair of Visual Computing Friedrich-Alexander-University Erlangen-Nürnberg Erlangen Germany

Objectives. The elastic properties of the vocal folds have great influence on the primary sound and thus on the entire subsequent phonation process. Muscle contractions in the larynx can alter the elastic properties of the vocal fold tissue. Quasi-static ultrasound elastography is a non-destructive examination method that can be applied to ex-vivo vocal folds. In this work, porcine vocal folds were passively elongated and adducted and the changes of the elastic properties due to that manipulations were measured. Methods. Manipulations were performed by applying force to sewn-in sutures. Elongation was achieved by a suture attached to the thyroid cartilage, which was pulled forward by defined weights. Adduction was effected by two sutures exerting torque on the arytenoid cartilage. A series of ten specimens was examined and evaluated using a quasi-static elastography algorithm. In addition, the surface stretch was measured optically using tattooed reference points. Results. This study showed that the expected stiffening of the tissue during the manipulations can be measured using quasi-static ultrasound elastography. The measured effect of elongation and adduction, both of which result in stretching of the tissue, is stiffening. However, the relative change of specific manipulations is not the same for the same load on different larynges, but is rather related to stretch caused and other uninvestigated factors. Conclusion. The passive elongation and adduction of vocal folds stiffen the tissue of the vocal folds and can be measured using ultrasound elastography. © 2023 The Authors

关键词： Adduction Elastography Elongation Ex-vivo experiment Porcine larynges Vocal folds Voice

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HistoMSC: Density and topology analysis for AI-based visual annotation of histopathology whole slide images

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Computers in Biology and Medicine 2025年 190卷 109991-109991页

作者： Ahmad, Zahoor Al-Thelaya, Khaled Alzubaidi, Mahmood Joad, Faaiz Gilal, Nauman Ullah Mifsud, William Boughorbel, Sabri Pintore, Giovanni Gobbetti, Enrico Schneider, Jens Agus, Marco Division of Information and Computing Technology College of Science and Engineering Hamad Bin Khalifa University Qatar Foundation Doha Qatar Kite Pharma Santa MonicaCA United States Visual and Data-intensive Computing CRS4 Italy Qatar Computing Research Institute Hamad Bin Khalifa University Qatar Foundation Doha Qatar

We introduce an end-to-end framework for the automated visual annotation of histopathology whole slide images. Our method integrates deep learning models to achieve precise localization and classification of cell nuclei with spatial data aggregation to extend classes of sparsely distributed nuclei across the entire slide. We introduce a novel and cost-effective approach to localization, leveraging a U-Net architecture and a ResNet-50 backbone. The performance is boosted through color normalization techniques, helping achieve robustness under color variations resulting from diverse scanners and staining reagents. The framework is complemented by a YOLO detection architecture, augmented with generative methods. For classification, we use context patches around each nucleus, fed to various deep architectures. Sparse nuclei-level annotations are then aggregated using kernel density estimation, followed by color-coding and isocontouring. This reduces visual clutter and provides per-pixel probabilities with respect to pathology taxonomies. Finally, we use Morse–Smale theory to generate abstract annotations, highlighting extrema in the density functions and potential spatial interactions in the form of abstract graphs. Thus, our visualization allows for exploration at scales ranging from individual nuclei to the macro-scale. We tested the effectiveness of our framework in an assessment by six pathologists using various neoplastic cases. Our results demonstrate the robustness and usefulness of the proposed framework in aiding histopathologists in their analysis and interpretation of whole slide images. © 2025 The Authors

关键词： Image annotation

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Multi-modal classification of forest biodiversity potential from 2D orthophotos and 3D airborne laser scanning point clouds

arXiv

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arXiv 2025年

作者： Jensen, Simon B. Oehmcke, Stefan Møgelmose, Andreas Madadi, Meysam Igel, Christian Escalera, Sergio Moeslund, Thomas B. Visual Analysis and Perception Laboratory Aalborg University Denmark Pioneer Centre for Artificial Intelligence Denmark Department of Computer Science Copenhagen University Denmark Institute for Visual & Analytic Computing Rostock University Germany University of Barcelona and Computer Vision Center Spain

Accurate assessment of forest biodiversity is crucial for ecosystem management and conservation. While traditional field surveys provide high-quality assessments, they are labor-intensive and spatially limited. This study investigates whether deep learning-based fusion of close-range sensing data from 2D orthophotos (12.5 cm resolution) and 3D airborne laser scanning (ALS) point clouds (8 points/m2) can enhance biodiversity assessment. We introduce the BioVista dataset, comprising 44 378 paired samples of orthophotos and ALS point clouds from temperate forests in Denmark, designed to explore multi-modal fusion approaches for biodiversity potential classification. Using deep neural networks (ResNet for orthophotos and PointVector for ALS point clouds), we investigate each data modality's ability to assess forest biodiversity potential, achieving mean accuracies of 69.4% and 72.8%, respectively. We explore two fusion approaches: a confidence-based ensemble method and a feature-level concatenation strategy, with the latter achieving a mean accuracy of 75.5%. Our results demonstrate that spectral information from orthophotos and structural information from ALS point clouds effectively complement each other in forest biodiversity assessment. © 2025, CC BY.

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Semantic-oriented visual Prompt Learning for Class Incremental Learning

Semantic-oriented Visual Prompt Learning for Class Increment...

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International Conference on Acoustics, Speech, and Signal Processing (ICASSP)

作者： Shuai Guo Yang Gu Yuan Ma Yingwei Zhang Weining Weng Jun Liu Weiwei Dai Yiqiang Chen Beijing Key Laboratory of Mobile Computing and Pervasive Device Institute of Computing Technology Chinese Academy of Sciences Beijing China University of Chinese Academy of Sciences Beijing China Institute of Digital Ophthalmology and Visual Science Changsha Aier Eye Hospital Changsha China Peng Cheng Laboratory Shenzhen China

ISBN: (数字)9798350368741

ISBN: (纸本)9798350368758

Class-incremental learning (CIL) enables models to continuously learn new classes while addressing catastrophic forgetting. With the introduction of pre-trained models, new tuning paradigms have emerged for CIL. This paper revisits parameter-efficient fine-tuning (PEFT) methods in the context of incremental learning. Prior studies reveal that PEFT methods’ extended parameters do not directly contribute to semantic perception, limiting performance with significant category and domain gaps. To address this, we propose semantic-oriented visual prompt learning (SVPL), which enhances semantic perception and improves task-specific knowledge extraction. SVPL assigns learnable prompts to each class, using a contrastive group alignment to align prompts to task-specific semantic spaces, thus preserving relationships between old and new knowledge. Additionally, hierarchical semantic delivery allows the semantic transformation of prompt groups from shallow to deep layers to facilitate efficient knowledge mining and enable effective learning of new knowledge. Extensive experimental results on five benchmarks demonstrate the superior performance of our methods.

关键词： visualization Incremental learning Limiting Semantics Benchmark testing Transformers Stability analysis Acoustics Speech processing Tuning

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TC-GS: Tri-plane based Compression for 3D Gaussian Splatting

arXiv

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arXiv 2025年

作者： Wang, Taorui Yu, Zitong Xu, Yong Shenzhen Key Laboratory of Visual Object Detection and Recognition Harbin Institute of Technology Shenzhen China School of Computing and Information Technology Great Bay University China Dongguan Key Laboratory for Intelligence and Information Technology China

Recently, 3D Gaussian Splatting (3DGS) has emerged as a prominent framework for novel view synthesis, providing high fidelity and rapid rendering speed. However, the substantial data volume of 3DGS and its attributes impede its practical utility, requiring compression techniques for reducing memory cost. Nevertheless, the unorganized shape of 3DGS leads to difficulties in compression. To formulate unstructured attributes into normative distribution, we propose a well-structured tri-plane to encode Gaussian attributes, leveraging the distribution of attributes for compression. To exploit the correlations among adjacent Gaussians, K-Nearest Neighbors (KNN) is used when decoding Gaussian distribution from the Triplane. We also introduce Gaussian position information as a prior of the position-sensitive decoder. Additionally, we incorporate an adaptive wavelet loss, aiming to focus on the high-frequency details as iterations increase. Our approach has achieved results that are comparable to or surpass that of SOTA 3D Gaussians Splatting compression work in extensive experiments across multiple datasets. The codes is available at TC-GS. Copyright © 2025, The Authors. All rights reserved.

关键词： Nearest neighbor search

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Meta-Transfer Learning Based Cross-Domain Gesture Recognition Using WiFi Channel State Information

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IEEE Transactions on Consumer Electronics 2025年

作者： Dai, Penglin Zhou, Junfei Ma, Jialong Zhang, Hao Wu, Xiao Southwest Jiaotong University School of Computing and Artificial Intelligence Chengdu611756 China Ministry of Education Engineering Research Center of Sustainable Urban Intelligent Transportation China Tangshan Institute of Southwest Jiaotong University Tangshan063000 China Chongqing University of Posts and Telecommunications College of Computer Science and Technology Key Laboratory of Data Engineering and Visual Computing Chongqing400065 China

Gesture recognition plays a crucial role in a wide range of consumer electronics applications, including human-computer interaction and virtual reality, by enabling the identification and interpretation of human gestures. In recent times, WiFi-based gesture recognition has garnered significant attention due to its privacy protection and unobtrusive nature. However, this approach heavily depends on neural network-based models and is notably influenced by environmental conditions, such as specific location and orientation. To address these environmental impacts, we propose a network framework that leverages transfer learning and meta-learning. The primary focus is on utilizing transfer learning to train a convolutional neural network (ResNet) for feature extraction, enabling the extraction of domain-independent features specifically related to gestures, rather than being influenced by environmental factors. Additionally, we employ the meta-learning algorithm MAML to train the fully connected network for gesture classification. Following training, a small set of samples can be utilized for rapid adaptation to diverse domains, maintaining high accuracy across different domains to achieve cross-domain gesture recognition. Our performance evaluation is based on the Widar 3.0 dataset, encompassing both in-domain and cross-domain scenarios. The simulation results demonstrate that our proposed algorithm surpasses Widar3.0 and WiGRUNT by approximately 7.9% and 1.12% in gesture recognition accuracy across all scenarios. © 2025 IEEE.

关键词： Wi-Fi

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Named Entity Recognition for Serbian Legal Documents: Design, Methodology and Dataset Development

arXiv

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arXiv 2025年

作者： Kalušev, Vladimir Brkljač, Branko Visual Computing & Perception Group The Institute for Artificial Intelligence Research and Development of Serbia Novi Sad Serbia Dept. of Power Electronic and Telecommunication Engineering Faculty of Technical Sciences University of Novi Sad Novi Sad Serbia

Recent advancements in the field of natural language processing (NLP) and especially large language models (LLMs) and their numerous applications have brought research attention to design of different document processing tools and enhancements in the process of document archiving, search and retrieval. Domain of official, legal documents is especially interesting due to vast amount of data generated on the daily basis, as well as the significant community of interested practitioners (lawyers, law offices, administrative workers, state institutions and citizens). Providing efficient ways for automation of everyday work involving legal documents is therefore expected to have significant impact in different fields. In this work we present one LLM based solution for Named Entity Recognition (NER) in the case of legal documents written in Serbian language. It leverages on the pre-trained bidirectional encoder representations from transformers (BERT), which had been carefully adapted to the specific task of identifying and classifying specific data points from textual content. Besides novel dataset development for Serbian language (involving public court rulings), presented system design and applied methodology, the paper also discusses achieved performance metrics and their implications for objective assessment of the proposed solution. Performed cross-validation tests on the created manually labeled dataset with mean F1 score of 0.96 and additional results on the examples of intentionally modified text inputs confirm applicability of the proposed system design and robustness of the developed NER *** Codes 68T10, 68T30, 68T35, 68T50, 91F20 © 2025, CC BY.

关键词： Natural language processing systems

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XML3D and Xflow Combining Declarative 3D for the Web with Generic Data Flows

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IEEE COMPUTER GRAPHICS AND APPLICATIONS 2013年第5期33卷 38-47页

作者： Klein, Felix Sons, Kristian Rubinstein, Dmitri Slusallek, Philipp Intel Visual Computing Institute|c|

Researchers have combined XML3D, which provides declarative, interactive 3D scene descriptions based on HTML5, with Xflow, a language for declarative, high-performance data processing. The result lets Web developers c... 详细信息

关键词： River Trail Web3D WebGL XML3D Xflow computer graphics data processing parallel JavaScript

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EventEgo3D++: 3D Human Motion Capture from a Head-Mounted Event Camera

arXiv

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arXiv 2025年

作者： Millerdurai, Christen Akada, Hiroyasu Wang, Jian Luvizon, Diogo Pagani, Alain Stricker, Didier Theobalt, Christian Golyanik, Vladislav Visual Computing and Artificial Intelligence Max Planck Institute for Informatics SIC Stuhlsatzenhausweg E1 4 Saarland Saarbrücken66123 Germany Trippstadter Str. 122 Rhineland-Palatinate Kaiserslautern67663 Germany

Monocular egocentric 3D human motion capture remains a significant challenge, particularly under conditions of low lighting and fast movements, which are common in head-mounted device applications. Existing methods that rely on RGB cameras often fail under these conditions. To address these limitations, we introduce EventEgo3D++, the first approach that leverages a monocular event camera with a fisheye lens for 3D human motion capture. Event cameras excel in high-speed scenarios and varying illumination due to their high temporal resolution, providing reliable cues for accurate 3D human motion capture. EventEgo3D++ leverages the LNES representation of event streams to enable precise 3D reconstructions. We have also developed a mobile head-mounted device (HMD) prototype equipped with an event camera, capturing a comprehensive dataset that includes real event observations from both controlled studio environments and in-the-wild settings, in addition to a synthetic dataset. Additionally, to provide a more holistic dataset, we include allocentric RGB streams that offer different perspectives of the HMD wearer, along with their corresponding SMPL body model. Our experiments demonstrate that EventEgo3D++ achieves superior 3D accuracy and robustness compared to existing solutions, even in challenging conditions. Moreover, our method supports real-time 3D pose updates at a rate of 140Hz. This work is an extension of the EventEgo3D approach (CVPR 2024) and further advances the state of the art in egocentric 3D human motion capture. For more details, visit the project page at https://***. Copyright © 2025, The Authors. All rights reserved.

关键词： Motion capture

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Virtual reconstruction of the Red Room exhibition

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Digital Applications in Archaeology and Cultural Heritage 2025年 37.0卷

作者： Guthe, Michael Mühlnikel, Marcus University of Bayreuth Visual Computing Universitätsstraße 30 Bavaria Bayreuth 95447 Germany University of Bayreuth Institute for Franconian Regional History Marktplatz 1 Bavaria Thurnau 95349 Germany

Museums increasingly use interactive installations to enhance exhibitions with additional content. Virtual reality can give the visitor access to remote places and bring the past back to life. This is especially interesting when artifacts cannot be brought back since they were sold or otherwise lost. In this project, we have partially reconstructed the Giech's family exhibition in the Red Room of Thurnau Castle. The exhibition ended when the family had to sell the exhibits in the 19th century because of financial problems. The goal of the project is to fully reconstruct the part of the exhibition that was shown in the Red Room based on a painting and the list of artifacts. While museums explain exhibits using information boards, the visitor of the Giech's family exhibition would have been guided by the earl himself. Therefore, we used virtual reality interaction techniques to make the exhibition more immersive and accessible. © 2025

关键词： Human–computer interfaces Virtual museum

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