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Epi-illumination tomographic quantitative phase imaging identifies brain tumor margins

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Label-free biomedical Imaging and Sensing, LBIS 2021

作者： Costa, Paloma Casteleiro Guang, Zhe Ledwig, Patrick Zhang, Zhaobin Neill, Stewart Olson, Jeffrey J. Robles, Francisco E. School of Electrical and Computer Engineering Georgia Institute of Technology AtlantaGA30332 United States Wallace H. Coulter Department of Biomedical Engineering Georgia Institute of Technology Emory University AtlantaGA30332 United States Winship Cancer Institute Emory University AtlantaGA30322 United States Department of Neurosurgery Emory University School of Medicine AtlantaGA30322 United States Department of Pathology and Laboratory Medicine Emory University School of Medicine AtlantaGA30322 United States

ISBN: (纸本)9781510641457

The first-line treatment for brain cancer is surgery, which focuses on maximizing the percentage of the tumor removed during surgery (i.e., extent of resection) while minimizing damage to healthy brain tissue. Data show that extent of resection is one of the most critical factors associated with prolonged survival. However, differentiating between tumor and healthy tissue intraoperatively remains a significant clinical challenge, resulting in an exceedingly low 5-year survival rate of only ~35%. In this work, we show that quantitative oblique back illumination microscopy (qOBM), a novel label-free optical imaging technique that achieves tomographic quantitative phase imaging (QPI) in thick scattering samples, clearly differentiates between tumor and healthy tissue. Using a 9L gliosarcoma rat tumor model, we show that quantitative image features from qOBM provide a robust set of biomarkers for disease. In addition, tumor regions, including diffuse tumor, and healthy brain structures, show excellent structural agreement with H&E stained and sliced brightfield images, the gold standard for cancer detection. The unique attribute of qOBM—low-cost, easy-to-use, label-free, and real-time—make this technology ideally suited to help guide neurosurgery and address this important unmet need. Here we describe our free-space qOBM system and present quantitative results from the 9L gliosarcoma rat tumor model. © 2021 SPIE.

关键词： Brain

Multimodal imaging of the mouse eye using visible light photoacoustic ophthalmoscopy and near-infrared-II optical coherence tomography

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arXiv 2023年

作者： Haindl, Richard Bellemo, Valentina Rajendran, Praveenbalaji Tan, Bingyao Liu, Mengyang Zhou, Qifa Leitgeb, Rainer A. Drexler, Wolfgang Schmetterer, Leopold Pramanik, Manojit School of Chemistry Chemical Engineering and Biotechnology Nanyang Technological University 62 Nanyang Drive Singapore Singapore Centre for Medical Physics and Biomedical Engineering Medical University of Vienna Währinger Gürtel 18-20/4L Vienna Austria Singapore Eye Research Institute Singapore National Eye Centre Singapore Singapore Program Nanyang Technological University Singapore Singapore Department of Radiation Oncology Stanford University StanfordCA94305 United States University of Southern California Department of Biomedical Engineering Los AngelesCA90033 United States Ophthalmology and Visual Sciences Academic Clinical Program Duke-NUS Medical School National University of Singapore Singapore Department of Clinical Pharmacology Medical University Vienna Vienna Austria Institute of Molecular and Clinical Ophthalmology Basel Switzerland Department of Electrical and Computer Engineering Iowa State University AmesIA50011 United States

Non-invasive imaging plays a crucial role in diagnosing and studying eye diseases. However, existing photoacoustic ophthalmoscopy (PAOM) techniques in mice have limitations due to handling restrictions, suboptimal optical properties, limited availability of light sources and permissible light fluence at the retina. This study introduces an innovative approach that utilizes Rose Bengal, a contrast agent, to enhance PAOM contrast. This enables visualization of deeper structures like the choroidal microvasculature and sclera in the mouse eye using visible light. The integration of near-infrared-II optical coherence tomography (NIR-II OCT) provides additional tissue contrast and insights into potential NIR-II PAOM capabilities. To optimize imaging, we developed a cost-effective 3D printable mouse eye phantom and a fully 3D printable tip/tilt mouse platform. This solution elevates PAOM to a user-friendly technology, which can be used to address pressing research questions concerning several ocular diseases such as myopia, glaucoma and/or age-related macular degeneration in the future. © 2023, CC BY.

关键词： Optical tomography

Transfer learning for future wireless networks: A comprehensive survey

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arXiv 2021年

作者： Nguyen, Cong T. Van Huynh, Nguyen Chu, Nam H. Saputra, Yuris Mulya Hoang, Dinh Thai Nguyen, Diep N. Pham, Quoc-Viet Niyato, Dusit Dutkiewicz, Eryk Hwang, Won-Joo School of Electrical and Data Engineering University of Technology Sydney SydneyNSW2007 Australia Research Institute of Computer Information and Communication Pusan National University Busan46241 Korea Republic of School of Computer Science and Engineering Nanyang Technological University Singapore639798 Singapore Department of Biomedical Convergence Engineering Pusan National University Yangsan50612 Korea Republic of

With outstanding features, Machine Learning (ML) has become the backbone of numerous applications in wireless networks. However, the conventional ML approaches face many challenges in practical implementation, such as the lack of labeled data, the constantly changing wireless environments, the long training process, and the limited capacity of wireless devices. These challenges, if not addressed, can impede the effectiveness and applicability of ML in wireless networks. To address these problems, Transfer Learning (TL) has recently emerged to be a promising solution. The core idea of TL is to leverage and synthesize distilled knowledge from similar tasks as well as from valuable experiences accumulated from the past to facilitate the learning of new problems. Doing so, TL techniques can reduce the dependence on labeled data, improve the learning speed, and enhance the ML methods' robustness to different wireless environments. This article aims to provide a comprehensive survey on applications of TL in wireless networks. Particularly, we first provide an overview of TL including formal definitions, classification, and various types of TL techniques. We then discuss diverse TL approaches proposed to address emerging issues in wireless networks. The issues include spectrum management, localization, signal recognition, security, human activity recognition and caching, which are all important to next-generation networks such as 5G and beyond. Finally, we highlight important challenges, open issues, and future research directions of TL in future wireless networks. © 2021, CC BY-NC-SA.

关键词： Wireless networks

Angel's girl for blind painters: An efficient painting navigation system validated by multimodal evaluation approach

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arXiv 2021年

作者： Liu, Hang Hu, Menghan Chen, Yuzhen Li, Qingli Zhai, Guangtao Yang, Simon X. Zhang, Xiao-Ping Yang, Xiaokang The Shanghai Key Laboratory of Multidimensional Information Processing East China Normal University The Key Laboratory of Articial Intelligence Ministry of Education The Advanced Robotics and Intelligent Systems Laboratory School of Engineering University of Guelph The Department of Electrical Computer and Biomedical Engineering Ryerson University

For people who ardently love painting but unfortunately have visual impairments, holding a paintbrush to create a work is a very difficult task. People in this special group are eager to pick up the paintbrush, like Leonardo da Vinci, to create and make full use of their own talents. Therefore, to maximally bridge this gap, we propose a painting navigation system to assist blind people in painting and artistic creation. The proposed system is composed of cognitive system and guidance system. The system adopts drawing board positioning based on QR code, brush navigation based on target detection and bush real-time positioning. Meanwhile, this paper uses human-computer interaction on the basis of voice and a simple but efficient position information coding rule. In addition, we design a criterion to efficiently judge whether the brush reaches the target or not. According to the experimental results, the thermal curves extracted from the faces of testers show that it is relatively well accepted by blindfolded and even blind testers. With the prompt frequency of 1s, the painting navigation system performs best with the completion degree of 89% ± 8.37% and overflow degree of 347% ± 162.14%. Meanwhile, the excellent and good types of brush tip trajectory account for 74%, and the relative movement distance is 4.21 ± 2.51. This work demonstrates that it is practicable for the blind people to feel the world through the brush in their hands. In the future, we plan to deploy "Angle's Eyes" on the phone to make it more portable. The demo video of the proposed painting navigation system is available at: https://***/10.6084/***.9760004.v1. © 2021, CC BY.

关键词： Cognitive systems

Injectable wireless micro-device integrated with photodegradable hydrogel for deep tissue therapeutics 23

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Injectable wireless micro-device integrated with photodegrad...

23rd International Conference on Miniaturized Systems for Chemistry and Life Sciences, MicroTAS 2019

作者： Lian, Sophie Liu, Yi Lin, Rongzhou Ho, John S. Chen, Chia-Hung Department of Biomedical Engineering National University of Singapore Singapore Singapore Department of Electrical and Computer Engineering National University of Singapore Singapore

ISBN: (纸本)9781733419000

A drug delivery system that allows a spatial, flexible and precise control of drug delivery, whilst being minimally invasive has been widely researched, with light stimulated smart hydrogels appearing as an attractive platform. However, as light has limited penetration through biological tissues, we have developed an integrated micro-device comprising of a wireless powered light source, and a photodegradable hydrogel to enable for deep-tissue therapeutics. Midfield wireless power transfer is permitted by the micro-device's miniaturized size, allowing for a penetration depth of several centimetres. Release studies have also shown a sustainable, targeted and controllable cargo release. © 2019 CBMS-0001.

关键词： Tissue

Scattering fingerprints of two-state dynamics

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arXiv 2021年

作者： Dieball, Cai Krapf, Diego Weiss, Matthias Godec, Aljaž Mathematical bioPhysics Group Max Planck Institute for Biophysical Chemistry Göttingen Germany Electrical and Computer Engineering and School of Biomedical Engineering Colorado State University Fort CollinsCO United States Experimental Physics I University of Bayreuth Bayreuth Germany

Particle transport in complex environments such as the interior of living cells is often (transiently) non-Fickian or anomalous, that is, it deviates from the laws of Brownian motion. Such anomalies may be the result of small-scale spatio-temporal heterogeneities in, or viscoelastic properties of, the medium, molecular crowding, etc. Often the observed dynamics displays multi-state characteristics, i.e. distinct modes of transport dynamically interconverting between each other in a stochastic manner. Reliably distinguishing between single- and multi-state dynamics is challenging and requires a combination of distinct approaches. To complement the existing methods relying on the analysis of the particle’s mean squared displacement, position- or displacement-autocorrelation function, and propagators, we here focus on "scattering fingerprints" of multi-state dynamics. We develop a theoretical framework for two-state scattering signatures – the intermediate scattering function and dynamic structure factor – and apply it to the analysis of simple model systems as well as particle-tracking experiments in living cells. We consider inert tracer-particle motion as well as systems with an internal structure and dynamics. Our results may generally be relevant for the interpretation of state-of-the-art differential dynamic microscopy experiments on complex particulate systems, as well as inelastic or quasielastic neutron (incl. spin-echo) and X-ray scattering scattering probing structural and dynamical properties of macromolecules, when the underlying dynamics displays two-state transport. Copyright © 2021, The Authors. All rights reserved.

关键词： Brownian movement

Phantom-Based Ultrasound-ECG Deep Learning Framework for Prospective Cardiac Computed Tomography

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IEEE transactions on bio-medical engineering 2025年 PP卷 PP页

作者： Shambavi Ganesh Brooks D Lindsey Srini Tridandapani Pamela T Bhatti Georgia Institute of Technology School of Electrical and Computer Engineering AtlantaGA United States Georgia Institute of Technology Wallace H. Coulter Department of Biomedical Engineering AtlantaGA United States University of Alabama Department of Radiology BirminghamAL United States

OBJECTIVE:We present the first multimodal deep learning framework combining ultrasound (US) and electrocardiography (ECG) data to predict cardiac quiescent periods (QPs) for optimized computed tomography angiography gating (CTA). METHODS:The framework integrates a 3D convolutional neural network (CNN) for US data and an artificial neural network (ANN) for ECG data. A dynamic heart motion phantom, replicating diverse cardiac conditions, including arrhythmias, was used to validate the framework. Performance was assessed across varying QP lengths, cardiac segments, and motions to simulate real-world conditions. RESULTS:The multimodal US-ECG 3D CNN-ANN framework demonstrated improved QP prediction accuracy compared to single-modality ECG-only gating, achieving 96.87% accuracy compared to 85.56%, including scenarios involving arrhythmic conditions. Notably, the framework shows higher accuracy for longer QP durations (100 ms - 200 ms) compared to shorter durations (<100ms), while still outperforming single-modality methods, which often fail to detect shorter quiescent phases, especially in arrhythmic cases. Consistently outperforming single-modality approaches, it achieves reliable QP prediction across cardiac regions, including the whole phantom, interventricular septum, and cardiac wall regions. Analysis of QP prediction accuracy across cardiac segments demonstrated an average accuracy of 92% in clinically relevant echocardiographic views, highlighting the framework's robustness. CONCLUSION:Combining US and ECG data using a multimodal framework improves QP prediction accuracy under variable cardiac motion, particularly in arrhythmic conditions. SIGNIFICANCE:Since even small errors in cardiac CTA can result in non-diagnostic scans, the potential benefits of multimodal gating may improve diagnostic scan rates in patients with high and variable heart rates and arrhythmias.

关键词： Electrocardiography

Adaptive control for flow and volume regulation in multi-producer district heating systems

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arXiv 2021年

作者： Martinez, Juan Eduardo Machado Cucuzzella, Michele Pronk, Nina Scherpen, Jacquelien M.A. The Jan C. Willems Center for Systems and Control ENTEG Faculty of Science and Engineering University of Groningen Nijenborgh 4 Groningen9747 AG Netherlands The Department of Electrical Computer and Biomedical Engineering University of Pavia via Ferrata 5 Pavia27100 Italy

Flow and storage volume regulation is essential for the adequate transport and management of energy resources in district heating systems. In this letter, we propose a novel and suitably tailored-decentralized-adaptive control scheme addressing this problem whilst offering closed-loop stability guarantees. We focus on a system configuration comprising multiple heat producers, consumers and storage tanks exchanging energy through a common distribution network, which are features of modern and prospective district heating installations. The proposed controller is based on passivity, backstepping and (indirect) adaptive control theory. Copyright © 2021, The Authors. All rights reserved.

关键词： District heating

Deep learning in biomedical optics

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arXiv 2021年

作者： Tian, Lei Hunt, Brady Lediju Bell, Muyinatu A. Yi, Ji Smith, Jason T. Ochoa, Marien Intes, Xavier Durr, Nicholas J. Department of Electrical and Computer Engineering Boston University BostonMA United States Thayer School of Engineering Dartmouth College HanoverNH United States Department of Electrical and Computer Engineering Johns Hopkins University BaltimoreMD United States Department of Biomedical Engineering Johns Hopkins University BaltimoreMD United States Department of Computer Science Johns Hopkins University BaltimoreMD United States Department of Ophthalmology Johns Hopkins University BaltimoreMD United States Center for Modeling Simulation and Imaging in Medicine Rensselaer Polytechnic Institute

This article reviews deep learning applications in biomedical optics with a particular emphasis on image formation. The review is organized by imaging domains within biomedical optics and includes microscopy, fluorescence lifetime imaging, in vivo microscopy, widefield endoscopy, optical coherence tomography, photoacoustic imaging, diffuse tomography, and functional optical brain imaging. For each of these domains, we summarize how deep learning has been applied and highlight methods by which deep learning can enable new capabilities for optics in medicine. Challenges and opportunities to improve translation and adoption of deep learning in biomedical optics are also summarized. Copyright © 2021, The Authors. All rights reserved.

关键词： Optical tomography