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arXiv 2020年

作者： Yu, Evan M. Iglesias, Juan Eugenio Dalca, Adrian V. Sabuncu, Mert R. Nancy E. and Peter C. Meinig School of Biomedical Engineering Cornell University Martinos Center for Biomedical Imaging Massachusetts General Hospital Harvard Medical School Mit Centre for Medical Image Computing University College London School of Electrical and Computer Engineering Cornell University

Deep neural networks are powerful tools for biomedical image segmentation. These models are often trained with heavy supervision, relying on pairs of images and correspond-ing voxel-level labels. However, obtaining segmentations of anatomical regions on a large number of cases can be prohibitively expensive. Thus there is a strong need for deep learning-based segmentation tools that do not require heavy supervision and can continu-ously adapt. In this paper, we propose a novel perspective of segmentation as a discrete representation learning problem, and present a variational autoencoder segmentation strat-egy that is flexible and adaptive. Our method, called Segmentation Auto-Encoder (SAE), leverages all available unlabeled scans and merely requires a segmentation prior, which can be a single unpaired segmentation image. In experiments, we apply SAE to brain MRI scans. Our results show that SAE can produce good quality segmentations, particularly when the prior is good. We demonstrate that a Markov Random Field prior can yield significantly better results than a spatially independent prior. Our code is freely available at https://***/evanmy/sae. Copyright © 2020, The Authors. All rights reserved.

关键词： Image segmentation

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Is perfect filtering enough leading to perfect phase correction for dMRI data?

arXiv

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arXiv 2021年

作者： Feihong, Liu Junwei, Yang Xiaowei, He Luping, Zhou Jun, Feng Dinggang, Shen School of Information Science and Technology Northwest University Xi’an China School of Biomedical Engineering ShanghaiTech University Shanghai China Department of Computer Science and Technology University of Cambridge Cambridge United Kingdom State-Province Joint Engineering Research Center of Advanced Networking and Intelligent Information Services School of Information Science and Technology Northwest University Xi’an China School of Electrical and Information Engineering University of Sydney Sydney Australia Shanghai United Imaging Intelligence Co. Ltd. Shanghai China

Being complex-valued and low in signal-to-noise ratios, magnitude based diffusion MRI is confounded by the noise-floor that falsely elevates signal magnitude and incurs bias to the commonly used diffusion indices, such as fractional anisotropy (FA). To avoid noise-floor, most existing phase correction methods explore improving filters to estimate the noise-free background phase. In this work, after diving into the phase correction procedures, we argue that even a perfect filter is insufficient for phase correction because the correction procedures are incapable of distinguishing sign-symbols of noise, resulting in artifacts (i.e., arbitrary signal loss). With this insight, we generalize the definition of noise-floor to a complex polar coordinate system and propose a calibration procedure that could conveniently distinguish noise sign-symbols. The calibration procedure is conceptually simple and easy to implement without relying on any external technique, while keeping distinctly effective. Extensive experimental results, including those on both synthetic and real diffusion MRI data, demonstrate that the calibrated procedures successfully mitigate artifacts in diffusion MR images and FA maps, with improved accuracy on estimating FA in particular. Copyright © 2021, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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Quantifying cerebral autoregulation in patients with sickle cell disease using near-infrared spectroscopy

Quantifying cerebral autoregulation in patients with sickle ...

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Clinical and Translational Biophotonics, Translational 2020

作者： Wood, Sossena Fanta, Abeselom Dosunmu-Ogunbi, Atinuke Ruesch, Alexander Jonassaint, Jude Huppert, Theodore Novelli, Enrico M. Kainerstorfer, Jana M. Department of Biomedical Engineering Carnegie Mellon University 5000 Forbes Ave. PittsburghPA15213 United States Vascular Medicine Institute Department of Medicine University of Pittsburgh 200 Lothrop Street PittsburghPA15260 United States Department of Electrical and Computer Engineering University of Pittsburgh PittsburghPA15260 United States Carnegie Mellon Neuroscience Institute Carnegie Mellon University 4400 Fifth Avenue PittsburghPA15213 United States

This study aimed to quantify cerebral autoregulation (CA) in patients with sickle cell disease (SCD) (n=11) and healthy controls (n=14) using near-infrared spectroscopy. Patients and volunteers performed paced breathi... 详细信息

ISBN: (纸本)9781943580743

关键词： Near infrared spectroscopy

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Motion-tolerant remote respiration monitoring with a multi-camera configuration

Motion-tolerant remote respiration monitoring with a multi-c...

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Imaging Systems and Applications, ISA 2020 - Part of Imaging and Applied Optics Congress 2020

作者： Chu, Ryan Ringuette, Dene Zhu, Eric Mihailidis, Alex Levi, Ofer Institute of Biomaterials and Biomedical Engineering University of Toronto TorontoON Canada Krembil Research Institute TorontoONM5T 0S8 Canada Edward S. Rogers Sr. Department of Electrical & Computer Engineering University of Toronto TorontoON Canada Toronto Rehabilitation Institute University Health Network TorontoONM5G 2A2 Canada Department of Occupational Science and Occupational Therapy University of Toronto TorontoON Canada

We demonstrate a method of motion-tolerant respiratory rate monitoring using a multicamera system. These cameras utilize depth sensing and are mounted around the subject. Results show successful isolation of the respi... 详细信息

ISBN: (纸本)9781557528209

关键词： Cameras

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GardnerNet: An Interpretable Deep Learning Model for Quantitative Human Blastocyst Evaluation - A Retrospective Model Development and Validation Study

SSRN

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SSRN 2024年

作者： Liu, Hang Chen, Longbin Shan, Guanqiao Sun, Chen Liao, Hongqing Lu, Changfu Zhang, Shuoping Dong, Shaonan Xu, Xinxin Yan, Qiuyun Gong, Fei Zhang, Zhuoran Dai, Changsheng Chen, Wenyuan Song, Haocong Chen, Lei Sun, Haixiang Wang, Shanshan Lin, Ge Sun, Yu Gu, Yifan Department of Mechanical and Industrial Engineering University of Toronto 5 King’s College Road TorontoONM5S 3G8 Canada Institute of Reproductive and Stem Cell Engineering School of Basic Medical Science Central South University 172 Tongzipo Road Hunan Province Changsha China Hengyang Nanhua-Xinghui Reproductive Health Hospital 30 Jiefang Road Hunan Province Hengyang China The second Affiliated Hospital Hengyang Medical School University of South China 30 Jiefang Road Hunan Province Hengyang City China Reproductive & Genetic Hospital of CITIC-Xiangya 567 Tongzipo Road Hunan Province Changsha China NHC Key Laboratory of Human Stem Cell and Reproductive Engineering School of Basic Medical Science Central South University 172 Tongzipo Road Hunan Province Changsha China Clinical Research Center for Reproduction and Genetics in Hunan Province Reproductive & Genetic Hospital of CITIC-Xiangya 567 Tongzipo Road Hunan Province Changsha China School of Science and Engineering The Chinese University of Hong Kong-Shenzhen 2001 Longxiang Boulevard Longgang District Shenzhen China Institute of Robotics and Intelligent Systems Dalian University of Technolgy 2 Linggong Road Liaoning Province Dalian China Department of Computer Science University of Toronto 40 St George Street TorontoONM5S 2E4 Canada Center for Reproductive Medicine and Obstetrics and Gynecology Nanjing Drum Tower Hospital Nanjing University Medical School 321 Zhongshan Road Jiangsu Province Nanjing China National Engineering and Research Center of Human Stem Cell 8 Luyun Road Jiangsu Province Changsha China Department of Electrical and Computer Engineering 10 King’s College Road TorontoONM5S 3G8 Canada Institute of Biomedical Engineering University of Toronto 164 College Street TorontoONM5S 3G9 Canada

Background: Selecting the blastocyst with the highest potential for live birth from a cohort is crucial for the success of in vitro fertilization (IVF). While the Gardner and Schoolcraft morphological grading system, commonly known as the Gardner grading system, is widely used by embryologists worldwide, blastocysts having similar or the same inner cell mass (ICM) and trophectoderm (TE) grades cause challenges for embryologists in decision-making. Furthermore, human assessment is subjective and inconsistent in predicting which blastocysts have higher potential to result in live birth. This study aims to develop an interpretable, quantitative method aligned with the Gardner grading system, providing continuous scores that correlate with live birth outcomes, thereby assisting embryologists in improving blastocyst selection. Methods: In this retrospective study, we developed GardnerNet, an interpretable deep learning model that outputs expansion degree grade and continuous scores quantifying a blastocyst's ICM morphology and TE morphology, based on the Gardner grading system. The continuous ICM and TE scores were calculated by weighting each base grade's predicted probability and summing the predicted probabilities. To represent each blastocyst's overall potential for live birth, we combined the ICM and TE scores using their odds ratios (ORs) for live birth. We further assessed the correlation between the ICM score, TE score, and the OR-combined score (adjusted for expansion degree) with live birth rates by applying GardnerNet to blastocysts with known live birth outcomes. To test its generalizability, we also applied GardnerNet to an external IVF institution, accounting for variations in imaging conditions, live birth rates, and embryologists' experience levels. Findings: GardnerNet was developed using data from 2760 blastocysts with majority-voted grades for expansion degree, ICM, and TE. The model achieved mean area under the receiver operating characteristic curve

关键词： Risk assessment

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Correction to: Development of a dedicated 3D printed myocardial perfusion phantom: proof-of-concept in dynamic SPECT

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Medical & biological engineering & computing 2022年第6期60卷 1551-1553页

作者： Marije E Kamphuis Gijs J de Vries Henny Kuipers Marloes Saaltink Jacqueline Verschoor Marcel J W Greuter Riemer H J A Slart Cornelis H Slump Multi-Modality Medical Imaging (M3i) Group Faculty of Science and Technology Technical Medical Centre 2386 University of Twente P.O. Box 217 7500 AE Enschede The Netherlands. kamphuis@utwente.nl. Robotics and Mechatronics (RaM) Group Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. kamphuis@utwente.nl. Robotics and Mechatronics (RaM) Group Faculty of Electrical Engineering Mathematics and Computer Science Technical Medical Centre University of Twente Enschede The Netherlands. Department of Nuclear Medicine Ziekenhuis Groep Twente Hengelo The Netherlands. Medical Imaging Centre Department of Nuclear Medicine and Molecular Imaging University Medical Center Groningen University of Groningen Groningen The Netherlands. Biomedical Photonic Imaging Group Faculty of Science and Technology Technical Medical Centre University of Twente Enschede The Netherlands.

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Observer-based Controller Design for Systems with Derivative Inputs

Observer-based Controller Design for Systems with Derivative...

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Annual Allerton Conference on Communication, Control, and Computing

作者： Bahram Shafai Anahita Moradmand Sam Nazari Electrical and Computer Engineering as well as Biomedical Engineering Northeastern University Boston MA USA Department of Electrical and Computer Engineering Northeastern University Boston MA USA

This paper considers observer-based controller design for systems involving input derivatives. First, we analyze the class of systems with derivative inputs which appear naturally or in connection to other class of systems such as singular systems. Due to the presence of input derivatives, we provide a procedure to eliminate the derivative inputs in order to facilitate the process of stabilization by state feedback. The elimination procedure transfers the input derivatives in the output equations. However, we show that the observer can also be designed by using change of variables avoiding derivative inputs in the final observer equation. Consequently, we construct the observer based controller design and establish separation principle for input derivative systems. Numerical example is provided to support the theoretical result.

关键词： Observers Controllability State feedback Linear systems Observability Transfer functions

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An optical voltage sensor based on piezoelectric thin film for grid applications

arXiv

引用

arXiv 2021年

作者： Edmunds, Jordan L. Sonmezoglu, Soner Martens, Julien Von Meier, Alexandra Maharbiz, Michel M. Department of Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA94704 United States Laboratory for Biomedical Microtechnology University of Freiburg Freiburg Germany Department of Bioengineering University of California Berkeley BerkeleyCA94704 United States Chan Zuckerberg Biohub San FranciscoCA94158 United States

Continuous monitoring of voltages ranging from tens to hundreds of kV over environmental conditions, such as temperature, is of great interest in power grid applications. This is typically done via instrument transformers. These transformers, although accurate and robust to environmental conditions, are bulky and expensive, limiting their use in microgrids and distributed sensing applications. Here, we present a millimeter-sized optical voltage sensor based on piezoelectric aluminum nitride (AlN) thin film for continuous measurements of AC voltages rms(via capacitive division) that avoids the drawbacks of existing voltage-sensing transformers. This sensor operated with 110μW incident optical power from a low-cost LED achieved a resolution of 170mVrmsin a 5kHz bandwidth, a measurement inaccuracy of 0.04% due to sensor nonlinearity, and a gain deviation of +/-0.2% over the temperature range of ∼20-60°C. The sensor has a breakdown voltage of 100V, and its lifetime can meet or exceed that of instrument transformers when operated at voltages rms. We believe that our sensor has the potential to reduce the cost of grid monitoring, providing a path towards more distributed sensing and control of the grid. Copyright © 2021, The Authors. All rights reserved.

关键词： III-V semiconductors

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Network-Aware 5G Edge Computing for Object Detection: Augmenting Wearables to "See" More, Farther and Faster

arXiv

引用

arXiv 2021年

作者： Yuan, Zhongzheng Azzino, Tommy Hao, Yu Lyu, Yixuan Pei, Haoyang Boldini, Alain Mezzavilla, Marco Beheshti, Mahya Porfiri, Maurizio Hudson, Todd Seiple, William Fang, Yi Rangan, Sundeep Wang, Yao Rizzo, J.R. Department of Electrical and Computer Engineering Tandon School of Engineering New York University BrooklynNY11201 United States Department of Mechanical and Aerospace Engineering Tandon School of Engineering New York University BrooklynNY11201 United States Department of Rehabilitation Medicine NYU Langone Health New YorkNY10016 United States Department of Biomedical Engineering Tandon School of Engineering New York University NY11201 United States Lighthouse Guild New YorkNY10023 United States Department of Ophthalmology NYU Grossman School of Medicine New YorkNY10016 United States Department of Neurology NYU Langone Health New YorkNY10016 United States

Advanced wearable devices are increasingly incorporating high-resolution multi-camera systems. As state-of-the-art neural networks for processing the resulting image data are computationally demanding, there has been a growing interest in leveraging fifth generation (5G) wireless connectivity and mobile edge computing for offloading this processing closer to end-users. To assess this possibility, this paper presents a detailed simulation and evaluation of 5G wireless offloading for object detection in the case of a powerful, new smart wearable called VIS4ION, for the Blind-and-Visually Impaired (BVI). The current VIS4ION system is an instrumented book-bag with high-resolution cameras, vision processing, and haptic and audio feedback. The paper considers uploading the camera data to a mobile edge server to perform real-time object detection and transmitting the detection results back to the wearable. To determine the video requirements, the paper evaluates the impact of video bit rate and resolution on object detection accuracy and range. A new street scene dataset with labeled objects relevant to BVI navigation is leveraged for analysis. The vision evaluation is combined with a full-stack wireless network simulation to determine the distribution of throughputs and delays with real navigation paths and ray-tracing from new high-resolution 3D models in an urban environment. For comparison, the wireless simulation considers both a standard 4G-Long Term Evolution (LTE) sub-6-GHz carrier and high-rate 5G millimeter-wave (mmWave) carrier. The work thus provides a thorough and detailed assessment of edge computing for object detection with mmWave and sub-6-GHz connectivity in an application with both high bandwidth and low latency requirements. © 2021, CC BY.

关键词： Object detection

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Publisher Correction: Energy efficient perching and takeoff of a miniature rotorcraft

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Communications engineering 2023年第1期2卷 1页

作者： Yi-Hsuan Hsiao Yufeng Chen Songnan Bai Huaiyuan Jia Runze Ding Pakpong Chirarattananon Yongsen Zhou Zuankai Wang Department of Electrical Engineering and Computer Science Massachusetts Institute of Technology Cambridge MA USA Department of Biomedical Engineering City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong SAR China Department of Mechanical Engineering City University of Hong Kong Tat Chee Avenue Kowloon Tong Hong Kong SAR China Department of Mechanical Engineering The Hong Kong Polytechnic University Hung Hom Kowloon Hong Kong SAR China

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