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Optical Coherence Tomography and Coherence Domain Optical Methods in Biomedicine XXV 2021

作者： Zurauskas, Mantas Iyer, Rishyashring R. Boppart, Stephen A. Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign UrbanaIL United States Department of Electrical and Computer Engineering University of Illinois at Urbana-Champaign UrbanaIL United States Department of Bioengineering University of Illinois at Urbana-Champaign ChampaignIL United States Cancer Center at Illinois University of Illinois at Urbana-Champaign UrbanaIL United States Carle Illinois College of Medicine University of Illinois at Urbana-Champaign ChampaignIL United States

ISBN: (数字)9781510640962

ISBN: (纸本)9781510640955

One limitation of phase shifting optical coherence microscopy (OCM) is that any changes in imaging conditions, caused by either system-level instability or movement of dynamic samples, will inevitably lead to reduction in image quality. Here we present a novel implementation of OCM which permits accurate measurements of phase and intensity, by simultaneously capturing four phase-shifted images on a single camera sensor. Uniquely, our approach enables probing the sample with unpolarized light, producing four phase-shifted interferograms, separated by Ïin two orthogonally polarized detection channel pairs. The proposed set-up is compatible with spatially incoherent illumination sources, enabling high resolution imaging due to its inherently reduced susceptibility to speckle noise. By simultaneously capturing the four phase-shifted images on a single CCD camera chip we demonstrate the capacity to acquire stable phase recordings with a phase sensitivity of 0.1 nm rms error at 500 Hz frame rates, a field-of-view of 250x250 μm, and 1μm lateral resolution. Instantaneous, coherence-gated, phase-sensitive imaging at high frame rates enables observations of the dynamics in cells and tissues, providing instant feedback on metabolic activity and tissue states. We present the novel design and methodology that enables ultrasensitive label-free coherence-gated measurements of intracellular dynamics in cells and cellular networks. © 2021 SPIE.

关键词： CCD cameras

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Deep learning-based framework for cardiac function assessment in embryonic zebrafish from heart beating videos

arXiv

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arXiv 2021年

作者： Naderi, Amir Mohammad Bu, Haisong Su, Jingcheng Huang, Mao-Hsiang Vo, Khuong Torres, Ramses Seferino Trigo Chiao, J.-C. Lee, Juhyun Lau, Michael P.H. Xu, Xiaolei Cao, Hung Department of Electrical Engineering and Computer Science University of California IrvineCA United States Department of Biochemistry and Molecular Biology Department of Cardiovascular Medicine Mayo Clinic RochesterMN United States Department of Biomechatronics Engineering National Taiwan University Taipei Taiwan Department of Computer Science University of California IrvineCA United States Department of Biomedical Engineering University of California IrvineCA United States Department of Electrical and Computer Engineering Southern Methodist University DallasTX United States Department of Bioengineering University of Texas ArlingtonTX United States Sensoriis Inc. EdmondsWA United States Electrical and Biomedical Engineering University of California Irvine IrvineCA92697 United States

Zebrafish is a powerful and widely-used model system for a host of biological investigations including cardiovascular studies and genetic screening. Zebrafish are readily assessable during developmental stages;however, the current methods for quantification and monitoring of cardiac functions mostly involve tedious manual work and inconsistent estimations. In this paper, we developed and validated a Zebrafish Automatic Cardiovascular Assessment Framework (ZACAF) based on a U-net deep learning model for automated assessment of cardiovascular indices, such as ejection fraction (EF) and fractional shortening (FS) from microscopic videos of wildtype and cardiomyopathy mutant zebrafish embryos. Our approach yielded favorable performance with accuracy above 90% compared with manual processing. We used only black and white regular microscopic recordings with frame rates of 5-20 frames per second (fps);thus, the framework could be widely applicable with any laboratory resources and infrastructure. Most importantly, the automatic feature holds promise to enable efficient, consistent and reliable processing and analysis capacity for large amounts of videos, which can be generated by diverse collaborating teams. © 2021, CC BY.

关键词： Heart

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Deep learning-based image reconstruction in optical coherence tomography using undersampled spectral data

Deep learning-based image reconstruction in optical coherenc...

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Conference on Lasers and Electro-Optics (CLEO)

作者： Yijie Zhang Tairan Liu Manmohan Singh Ege Çetintaş Yilin Luo Yair Rivenson Kirill V. Larin Aydogan Ozcan Electrical and Computer Engineering Department University of California Los Angeles CA USA Bioengineering Department University of California Los Angeles CA USA California NanoSystems Institute (CNSI) University of California Los Angeles CA USA Department of Biomedical Engineering University of Houston Houston TX USA Department of Molecular Physiology and Biophysics Baylor College of Medicine University of Houston Houston TX USA Department of Surgery David Geffen School of Medicine University of California Los Angeles CA USA

We present a deep learning-based image reconstruction method in swept-source optical coherent tomography (OCT) using undersampled spectral data. This method can improve the imaging speed without the need for any hardw... 详细信息

ISBN: (数字)9781957171050

ISBN: (纸本)9781665466660

关键词： Optical coherence tomography Neural networks Optical computing Coherence Optical fiber networks Lasers and electrooptics Optical imaging

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Discrete frequency infrared vibrational circular dichroism spectroscopy & imaging

Discrete frequency infrared vibrational circular dichroism s...

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Novel Techniques in Microscopy, NTM 2021 - Part of Biophotonics Congress: Optics in the Life Sciences 2021

作者： Phal, Yamuna Yeh, Kevin Bhargava, Rohit Department of Electrical and Computer Engineering University of Illinois at Urbana Champaign 306 N. Wright St UrbanaIL61801 United States Departments of Bioengineering Chemistry Chemical and Biomolecular Engineering Mechanical Science and Engineering University of Illinois at Urbana-Champaign UrbanaIL61801 United States Cancer Center at Illinois University of Illinois at Urbana-Champaign UrbanaIL61801 United States Beckman Institute for Advanced Science and Technology University of Illinois at Urbana-Champaign 405 N. Mathews Ave UrbanaIL61801 United States

Vibrational Circular Dichroism (VCD) arises from chiroptical phenomena in biological samples. We demonstrate VCD imaging, a novel microscopy technique that can provide molecular- and spatially-specific chirality mappi... 详细信息

ISBN: (纸本)9781557528209

关键词： Dichroism

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Phase Correction of MR Spectroscopic Imaging Data Using Model-Based Signal Estimation and Extrapolation

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IEEE Transactions on Biomedical engineering 2025年 PP卷 PP页

作者： Jin, Wen Guo, Rong Li, Yudu Zhao, Yibo Li, Xin Zhu, Xiao-Hong Chen, Wei Liang, Zhi-Pei University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Department of Electrical and Computer Engineering Urbana IL United States University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Urbana IL United States Siemens Medical Solutions USA Inc. Malvern PA United States University of Illinois at Urbana-Champaign Beckman Institute for Advanced Science and Technology Department of Bioengineering National Center for Supercomputing Applications Urbana IL United States University of Minnesota Department of Radiology Center for Magnetic Resonance Research Minneapolis MN United States

Objective: To develop an effective method for phase correction of magnetic resonance spectroscopic imaging (MRSI) data. Methods: In many MRSI applications, it is desirable to generate absorption-mode spectra, which requires correction of phase errors in the measured MRSI data. Conventional phase correction methods are sensitive to measurement noise and baseline distortion, often resulting in distorted absorption-mode spectra from MRSI data with low-SNR and long acquisition dead time. This paper proposed a novel model-based method for improved phase correction of MRSI data. The proposed method determined the zeroth-order phase and acquisition dead time using a Lorentzian-based spectral model and performed signal extrapolation using a generalized series model. Absorption-mode spectra were then generated from the phase-corrected and extrapolated MRSI data. Results: The proposed method was evaluated using both simulated data and experimental data acquired from human subjects in multi-nuclei ( ³¹P, ²H, and ¹H) MRSI experiments. Simulation results demonstrated improved parameter estimation accuracy by the proposed method under various noise levels and dead times. The proposed method also consistently generated high-quality absorption-mode spectra with minimal spectral distortions from experimental data. The proposed method was compared with state-of-the-art methods (including the entropy method and LCModel method) and showed more robust phase correction performance with less spectral distortions. Conclusion: This paper introduced a novel method for phase correction of MRSI data. Results from simulated and in vivo data demonstrated that high-quality absorption-mode spectra could be obtained using the proposed method. Significance: This method will provide a useful tool for processing MRSI data. © 1964-2012 IEEE.

关键词： Absorption-mode spectrum generalized series model MRSI phase correction subspace model

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Noninvasive multichannel urodynamic system: Obtaining cutaneous electrical signals from the human urinary bladder

Lifestyle Medicine

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Lifestyle Medicine 2024年第1期5卷

作者： Kurniawan, Jonas F. Lee, Sanghee Le, Hoang-Kim Nguyen, Andrew K. L. Sit, Nathan L. J. Pham, Timothy Tjhia, Boris Gottlieb, Ryan Li, Carleen Shin, Andrew J. Garcia, Hassler Bueno Wu, Vincent M. Mendoza, Tris R DiPina, Thomas Ornelas, Gladys Chiang, George Jamieson, Christina A. M. Santiago-Lastra, Yahir Coleman, Todd P. Department of Bioengineering University of California San Diego La Jolla CA United States Materials Science and Engineering Program University of California San Diego La Jolla CA United States Department of Bioengineering Stanford University Stanford CA United States Department of Urology University of California San Diego La Jolla CA United States Pediatric Urology Rady Children's Hospital San Diego San Diego CA United States Department of Urology Baylor Scott & White Temple TX United States Department of Physics University of California San Diego La Jolla CA United States Department of Electrical and Computer Engineering University of California San Diego La Jolla CA United States Department of Nanoengineering University of California San Diego La Jolla CA United States Department of Materials Science and Engineering Stanford University Stanford CA United States Division of Pediatric Urology University of California San Diego La Jolla CA United States

We developed a high-resolution and noninvasive multichannel urodynamic system combined with a novel signal-processing algorithm tailored to extract electromyographic (EMG) activity from the urinary bladder. We utilized a flexible noninvasive biopotential recording system to collect an array of EMG signals from the urinary bladder of human subjects. This study also presents the use of an existing artifact rejection methodology to autonomously extract an EMG signal from an environment prone to motion artifacts. © 2023 The Authors. Lifestyle Medicine published by John Wiley & Sons Ltd.

关键词： electrical signal from the urinary bladder flexible electronics noninvasive multichannel urodynamic study voluntary voiding

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Early detection and classification of bacterial colonies using a Thin-Film-Transistor (TFT)-based image sensor and deep learning

Early detection and classification of bacterial colonies usi...

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Frontiers in Optics, FiO 2022

作者： Li, Yuzhu Liu, Tairan Koydemir, Hatice Ceylan Wang, Hongda O'Riordan, Keelan Bai, Bijie Haga, Yuta Kobashi, Junji Tanaka, Hitoshi Tamaru, Takaya Yamaguchi, Kazunori Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los AngelesCA90095 United States Bioengineering Department University of California Los Angeles90095 United States University of California Los AngelesCA90095 United States Department of Biomedical Engineering Texas A&M University College StationTX77843 United States Center for Remote Health Technologies and Systems Texas A&M University College StationTX77843 United States Department of Physics and Astronomy University of California Los AngelesCA90095 United States System Development Department Research & Development Division Japan Display Inc. Kanagawa243-0432 Japan Device Development Department Research & Development Division Japan Display Inc. Chiba297-8622 Japan R&D Planning Department Research & Development Division Japan Display Inc. Tokyo105-0003 Japan Department of Surgery University of California Los AngelesCA90095 United States

We report a rapid, automated, portable and high-throughput bacterial colony detection and classification system using a thin-film-transistor array and deep learning, achieving >12 hours of time savings compared to ...

ISBN: (纸本)9781557528209

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Author Correction: Dynamical flexible inference of nonlinear latent factors and structures in neural population activity

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Nature biomedical engineering 2025年第2期9卷 283页

作者： Hamidreza Abbaspourazad Eray Erturk Bijan Pesaran Maryam M Shanechi Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los Angeles CA USA. Departments of Neurosurgery Neuroscience and Bioengineering University of Pennsylvania Philadelphia PA USA. Ming Hsieh Department of Electrical and Computer Engineering Viterbi School of Engineering University of Southern California Los Angeles CA USA. shanechi@usc.edu. Thomas Lord Department of Computer Science Alfred E. Mann Department of Biomedical Engineering Neuroscience Graduate Program University of Southern California Los Angeles CA USA. shanechi@usc.edu.

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Image-guided breast biopsy of MRI-visible lesions with a hand-mounted motorised needle steering tool

arXiv

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arXiv 2021年

作者： Lagomarsino, Marta Groenhuis, Vincent Casadio, Maura Welleweerd, Marcel K. Siepel, Françoise J. Stramigioli, Stefano Laboratory Faculty of Electrical Engineering Mathematics and Computer Science University of Twente Drienerlolaan 5 Enschede7522NB Netherlands Department of Informatics Bioengineering Robotics and Systems Engineering University of Genoa Via Opera Pia 13 Genoa16145 Italy Department of Advanced Robotics Istituto Italiano di Tecnologia Genoa Italy Department of Electronics Information and Bioengineering Politecnico di Milano Milan Italy

A biopsy is the only diagnostic procedure for accurate histological confirmation of breast cancer. When sonographic placement is not feasible, a Magnetic Resonance Imaging(MRI)-guided biopsy is often preferred. The lack of real-time imaging information and the deformations of the breast make it challenging to bring the needle precisely towards the tumour detected in pre-interventional Magnetic Resonance (MR) images. The current manual MRI-guided biopsy workflow is inaccurate and would benefit from a technique that allows real-time tracking and localisation of the tumour lesion during needle insertion. This paper proposes a robotic setup and software architecture to assist the radiologist in targeting MR-detected suspicious tumours. The approach benefits from image fusion of preoperative images with intraoperative optical tracking of markers attached to the patient's skin. A hand-mounted biopsy device has been constructed with an actuated needle base to drive the tip toward the desired direction. The steering commands may be provided both by user input and by computer guidance. The workflow is validated through phantom experiments. On average, the suspicious breast lesion is targeted with a radius down to 2.3 mm. The results suggest that robotic systems taking into account breast deformations have the potentials to tackle this clinical challenge. Copyright © 2021, The Authors. All rights reserved.

关键词： Biopsy

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Plug-and-play stability for intracortical brain-computer interfaces: a one-year demonstration of seamless brain-to-text communication 23

Plug-and-play stability for intracortical brain-computer int...

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Proceedings of the 37th International Conference on Neural Information Processing Systems

作者： Chaofei Fan Nick Hahn Foram Kamdar Donald Avansino Guy H. Wilson Leigh Hochberg Krishna V. Shenoy Jaimie M. Henderson Francis R. Willett Department of Computer Science Stanford University Department of Neurosurgery Stanford University Howard Hughes Medical Institute at Stanford University Department of Neuroscience Stanford University School of Engineering and Carney Institute for Brain Science Brown University and VA RR & D Center for Neurorestoration and Neurotechnology VA Providence Healthcare System and Center for Neurotechnology and Neurorecovery Department of Neurology Massachusetts General Hospital Harvard Medical School Bio-X Program Stanford University and Department of Neurobiology Stanford University and Department of Bioengineering Stanford University and Wu Tsai Neurosciences Institute Stanford University and Howard Hughes Medical Institute at Stanford University and Department of Electrical Engineering Stanford University Department of Neurosurgery Stanford University and Wu Tsai Neurosciences Institute Stanford University

Intracortical brain-computer interfaces (iBCIs) have shown promise for restoring rapid communication to people with neurological disorders such as amyotrophic lateral sclerosis (ALS). However, to maintain high performance over time, iBCIs typically need frequent recalibration to combat changes in the neural recordings that accrue over days. This requires iBCI users to stop using the iBCI and engage in supervised data collection, making the iBCI system hard to use. In this paper, we propose a method that enables self-recalibration of communication iBCIs without interrupting the user. Our method leverages large language models (LMs) to automatically correct errors in iBCI outputs. The self-recalibration process uses these corrected outputs ("pseudo-labels") to continually update the iBCI decoder online. Over a period of more than one year (403 days), we evaluated our Continual Online Recalibration with Pseudo-labels (CORP) framework with one clinical trial participant. CORP achieved a stable decoding accuracy of 93.84% in an online handwriting iBCI task, significantly outperforming other baseline methods. Notably, this is the longest-running iBCI stability demonstration involving a human participant. Our results provide the first evidence for long-term stabilization of a plug-and-play, high-performance communication iBCI, addressing a major barrier for the clinical translation of iBCIs.

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