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arXiv 2022年

作者： Wang, Ke Doneva, Mariya Meineke, Jakob Amthor, Thomas Karasan, Ekin Tan, Fei Tamir, Jonathan I. Yu, Stella X. Lustig, Michael Electrical Engineering and Computer Sciences University of California Berkeley BerkeleyCA United States Philips Research Europe Hamburg Germany Bioengineering UC Berkeley-UCSF San FranciscoCA United States Chandra Family Department of Electrical and Computer Engineering The University of Texas at Austin AustinTX United States International Computer Science Institute BerkeleyCA United States Computer Science and Engineering University of Michigan Ann ArborMI United States

Magnetic Resonance Fingerprinting (MRF) is an efficient quantitative MRI technique that can extract important tissue and system parameters such as T1, T2, B0, and B1 from a single scan. This property also makes it attractive for retrospectively synthesizing contrast-weighted images. In general, contrast-weighted images like T1-weighted, T2-weighted, etc. can be synthesized directly from parameter maps through spin-dynamics simulation (i.e., Bloch or Extended Phase Graph models). However, these approaches often exhibit artifacts due to imperfections in the mapping, the sequence modeling, and the data acquisition. Here we propose a supervised learning-based method that directly synthesizes contrast-weighted images from the MRF data without going through the quantitative mapping and spin-dynamics simulation. To implement our direct contrast synthesis (DCS) method, we deploy a conditional Generative Adversarial Network (GAN) framework and propose a multi-branch U-Net as the generator. The input MRF data are used to directly synthesize T1-weighted, T2-weighted, and fluid-attenuated inversion recovery (FLAIR) images through supervised training on paired MRF and target spin echo-based contrast-weighted scans. In-vivo experiments demonstrate excellent image quality compared to simulation-based contrast synthesis and previous DCS methods, both visually as well as by quantitative metrics. We also demonstrate cases where our trained model is able to mitigate in-flow and spiral off-resonance artifacts that are typically seen in MRF reconstructions and thus more faithfully represent conventional spin echo-based contrast-weighted images. © 2022, CC0.

关键词： Generative adversarial networks

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Effects of Surface Passivation on CdZnTeSe Nuclear Detectors

Effects of Surface Passivation on CdZnTeSe Nuclear Detectors

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2021 IEEE Nuclear Science Symposium and Medical Imaging Conference, NSS/MIC 2021

作者： Egarievwe, Stephen U. Roy, Utpal N. Agbalagba, Ezekiel O. Davis, Amir H. Israel, Mordecai B. Alexander, Parion L. James, Ralph B. Alabama A and M University Nuclear Engineering and Radiological Science Center Department of Electrical Engineering and Computer Science AL35762 United States Brookhaven National Laboratory Department of Nonproliferation and National Security NY11973 United States Savannah River National Laboratory Science and Technology AikenSC29808 United States Federal University of Petroleum Resources Department of Physics Delta State Nigeria Stanford University Department of Bioengineering CA94305 United States University of South Alabama Department of Electrical and Computer Engineering MobileAL36688 United States Alabama A and M University Department of Biological and Environmental Sciences AL35762 United States

ISBN: (纸本)9781665421133

Cadmium zinc telluride selenide (CdZnTeSe) has shown great promise in reducing the cost of semiconductor nuclear detectors that can operate at room temperature without cryogenic cooling. This is due to the high yield of detector-grade materials in the CdZnTeSe crystal growth process, which can be attributed to the much smaller numbers of Te inclusions and grain boundary network in CdZnTeSe compared to other CdTe-based semiconductors such as CdZnTe. In the present work, we study the effects of surface passivation on CdZnTe detectors using a mixture of ammonium fluoride and hydrogen peroxide solution (NH4F + H2O2 + H2O). Detectors fabricated from CdZnTeSe crystals showed very good energy resolutions: 1.1% for the 662-keV gamma peak of 137Cs by Frisch-grid detectors, and 5.9% for the 59.6-keV gamma peak of 241Am by planar detectors. Experimental results show that the leakage current is increased immediately after passivation and then decreases as the surfaces stabilizes. The resistivity of the CdZnTeSe is of the order of 1010Ω-cm. The surface passivation improved the energy resolution of planar detector by 18% for the 59.6-keV gamma peak of 241Am. © 2021 IEEE.

关键词： Fluorine compounds

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Impulse data models for the inverse problem of electrocardiography

arXiv

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arXiv 2021年

作者： Peng, Tommy Malik, Avinash Bear, Laura R. Trew, Mark L. The Department of Electrical and Computer Engineering University of Auckland New Zealand IHU-LIRYC The Auckland Bioengineering Institute University of Auckland New Zealand

Objective: To develop, train and test neural networks for predicting heart surface potentials (HSPs) from body surface potentials (BSPs). The method re-frames traditional inverse problems of electrocardiography into regression problems, constraining the solution space by decomposing signals with multidimensional Gaussian impulse basis functions. Methods: Impulse HSPs were generated with single Gaussian basis functions at discrete heart surface locations and projected to corresponding BSPs using a volume conductor torso model. Both BSP (inputs) and HSP (outputs) were mapped to regular 2D surface meshes and used to train a neural network. Predictive capabilities of the network were tested with unseen synthetic and experimental data. Results: A dense full connected single hidden layer neural network was trained to map body surface impulses to heart surface Gaussian basis functions for reconstructing HSP. Synthetic pulses moving across the heart surface were predicted from the neural network with root mean squared error of 9.1 ± 1.4%. Predicted signals were robust to noise up to 20 dB and errors due to displacement and rotation of the heart within the torso were bounded and predictable. A shift of the heart 40 mm toward the spine resulted in a 4% increase in signal feature localization error. The set of training impulse function data could be reduced, and prediction error remained bounded. Recorded HSPs from in-vitro pig hearts were reliably decomposed using space-time Gaussian basis functions. Activation times calculated from predicted HSPs for left-ventricular pacing had a mean absolute error of 10.4 ± 11.4 ms. Other pacing scenarios were analyzed with similar success. Conclusion: Impulses from Gaussian basis functions are potentially an effective and robust way to train simple neural network data models for reconstructing HSPs from decomposed BSPs. Significance: The HSPs predicted by the neural network can be used to generate activation maps that non-invasively ident

关键词： Electrocardiography

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Digital synthesis of histological stains using micro-structured and multiplexed virtual staining of label-free tissue

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Light(Science & Applications) 2020年第1期9卷 1273-1285页

作者： Yijie Zhang Kevin de Haan Yair Rivenson Jingxi Li Apostolos Delis Aydogan Ozcan Electrical and Computer Engineering Department University of CaliforniaLos AngelesCA 90095USA Bioengineering Department University of CaliforniaLos AngelesCA 90095USA California NanoSystems Institute(CNSI) University of CaliforniaLos AngelesCA 90095USA Department of Computer Science University of CaliforniaLos AngelesCA 90095USA Department of Surgery David Geffen School of MedicineUniversity of CaliforniaLos AngelesCA 90095USA

Histological staining is a vital step in diagnosing various diseases and has been used for more than a century to provide contrast in tissue sections,rendering the tissue constituents visible for microscopic analysis by medical ***,this process is time consuming,labour intensive,expensive and destructive to the ***,the ability to virtually stain unlabelled tissue sections,entirely avoiding the histochemical staining step,has been demonstrated using tissue-stain-specific deep neural ***,we present a new deep-learning-based framework that generates virtually stained images using label-free tissue images,in which different stains are merged following a micro-structure map defined by the *** approach uses a single deep neural network that receives two different sources of information as its input:(1)autofluorescence images of the label-free tissue sample and(2)a“digital staining matrix”,which represents the desired microscopic map of the different stains to be virtually generated in the same tissue *** digital staining matrix is also used to virtually blend existing stains,digitally synthesizing new histological *** trained and blindly tested this virtual-staining network using unlabelled kidney tissue sections to generate micro-structured combinations of haematoxylin and eosin(H&E),Jones’silver stain,and Masson’s trichrome *** a single network,this approach multiplexes the virtual staining of label-free tissue images with multiple types of stains and paves the way for synthesizing new digital histological stains that can be created in the same tissue cross section,which is currently not feasible with standard histochemical staining methods.

关键词： network rendering synthesis

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BlurryScope: a cost-effective and compact scanning microscope for automated HER2 scoring using deep learning on blurry image data

arXiv

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arXiv 2024年

作者： Fanous, Michael John Seybold, Christopher Michael Chen, Hanlong Pillar, Nir Ozcan, Aydogan Electrical and Computer Engineering Department University of California Los Angeles90095 CA United States Mathematics Department University of California Los Angeles90095 CA United States Bioengineering Department University of California Los Angeles90095 CA United States University of California Los Angeles90095 CA United States Department of Surgery David Geffen School of Medicine University of California Los Angeles90095 CA United States

We developed a rapid scanning optical microscope, termed "BlurryScope", that leverages continuous image acquisition and deep learning to provide a cost-effective and compact solution for automated inspection and analysis of tissue sections. BlurryScope integrates specialized hardware with a neural network-based model to quickly process motion-blurred histological images and perform automated pathology classification. This device offers comparable speed to commercial digital pathology scanners, but at a significantly lower price point and smaller size/weight, making it ideal for fast triaging in small clinics, as well as for resource-limited settings. To demonstrate the proof-of-concept of BlurryScope, we implemented automated classification of human epidermal growth factor receptor 2 (HER2) scores on immunohistochemically (IHC) stained breast tissue sections, achieving concordant results with those obtained from a high-end digital scanning microscope. We evaluated this approach by scanning HER2-stained tissue microarrays (TMAs) at a continuous speed of 5,000 µm/s, which introduces bidirectional motion blur artifacts. These compromised images were then used to train our network models. Using a test set of 284 unique patient cores, we achieved blind testing accuracies of 79.3% and 89.7% for 4-class (0, 1+, 2+, 3+) and 2-class (0/1+, 2+/3+) HER2 score classification, respectively. BlurryScope automates the entire workflow, from image scanning to stitching and cropping of regions of interest, as well as HER2 score classification. We believe BlurryScope has the potential to enhance the current pathology infrastructure in resource-scarce environments, save diagnostician time and bolster cancer identification and classification across various clinical environments. Copyright © 2024, The Authors. All rights reserved.

关键词： Photomapping

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Biophysics of amplitude-modulated giga-hertz electromagnetic waves stimulation

Biophysics of amplitude-modulated giga-hertz electromagnetic...

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Asilomar Conference on Signals, Systems & computers

作者： Fatima Ahsan Aravind C. Govindaraju Robert M. Raphael Taiyun Chi Sameer A. Sheth Wayne Goodman Behnaam Aazhang Department of Electrical and Computer Engineering Rice University Houston TX USA Applied Physics Graduate Program Smalley-Curly Institute Rice University Houston TX Department of Bioengineering Rice University Houston TX USA Department of Neurosurgery Baylor College of Medicine Houston TX USA Menninger Department of Psychiatry and Behavioral Sciences Baylor College of Medicine Houston TX USA

This paper presents the biophysical modeling for neuronal stimulation caused by amplitude-modulated giga-hertz (GHz) electromagnetic (EM) waves. We model a 1D cable equation for electrical signal propagation in a vestibular ganglion neuronal fiber and use Hodgkin-Huxley formalism to model voltage-dependent channel conductances. We find out that for a given stimulation signal strength, the GHz waveform amplitude-modulated at a low frequency of Δf causes neuronal firing with the frequency of Δf whereas the continuous wave GHz did not elicit any neuronal firing. Moreover, the voltage-dependent channel gating dynamics of the Δf amplitude-modulated GHz stimulation matches that of a simple low frequency stimulation at Δf. Additionally, we find that the modulation depth controls the firing rate of the neurons. The significance of this property is that the amplitude modulation caused by the interference of two similar high frequency signals could be leveraged to focally excite neurons at depth without stimulating overlying cortical regions. These theoretical predictions based on the Hodgkin-Huxley model can later be tested experimentally.

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Design of Modular Readout Electronics for Cadmium Zinc Telluride (CZT) PET Imaging of the Plants Rhizosphere

Design of Modular Readout Electronics for Cadmium Zinc Tellu...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Muhammad Nasir Ullah Andrew Groll Derek Innes Shiva Abbaszadeh Craig S. Levin Department of Radiology Stanford University California USA Department of Radiology and Molecular Imaging Program at Stanford (MIPS) Stanford University California USA Department of Electrical and Computer Engineering University of California Santa Cruz Santa Cruz California USA Departments of Radiology Electrical Engineering Bioengineering Physics Molecular Imaging Program at Stanford MIPS) Stanford University Stanford California USA

To study and quantify the dynamic behavior of a plant’s soil-root interface (rhizosphere), we are developing a hybrid positron emission tomography-computed tomography (PET-CT) system to obtain in situ 3D images to help in modeling the Earth System Model (ESM) in a precise manner. ESM integrates the relevant aspects of the earth system to study the state of climate under various of conditions. The proposed system aims to understand the complex bi-directional flow of carbon in the rhizosphere by quantitatively measuring 11 C concentration. The rhizosphere imaging requires the creation of a PET system with high sensitivity and excellent spatial resolution; a dual panel geometry of cadmium zinc telluride (CZT) detectors with fine electrodes is being refined and scaled to a 4-panel system to answer the demands. This work focuses on the development, evaluation, and integration of the critical intermediate board (IB) needed to support approximately 5 thousand channels in the CZT PET system and provide modularity to the system. A Rigid-Flex PCB approach is adopted to design the IB. The rigid region will provide firm mechanical support for direct placement of the necessary electronic components and connectors, and the flex region will help to align the subsequent readout boards at the backend of the IB while maintaining the dense packing fraction at front-end where the CZT crystals are connected. Three CZT module (each module comprising of 2-crystals of 39x39 x5 mm 3 sandwiched in anode-cathode-cathode-anode configuration) along with 1-mm thick mechanical support on either side of modules will be directly attached to two IBs which forms one tray to modularize the entire system. This modularized design will help to assemble and dissemble the system in an efficient way and minimize the chance of damaging the crystal assemblies. This new IB design will address the troubleshooting/repairing experience and modularity issues that were taking significant amount of time and energy

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3D Dynamic Lensing via Enhanced Light-Sound Interactions

3D Dynamic Lensing via Enhanced Light-Sound Interactions

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CLEO: Science and Innovations, S and I 2022

作者： Chabok, Hamid Reza Lu, Thompson Mostaan, Mohammad Reza Bahari, Babak Jung, Pawel S. Christodoulides, Demetrios N. Khajavikhan, Mercedeh Department of Physics and Astronomy University of Southern California Los AngelesCA90089 United States Department of Bioengineering University of California 900 University Avenue RiversideCA92521 United States Department of Physics Simon Fraser University BurnabyBCV5A 1S6 Canada Department of Electrical and Computer Engineering University of Southern California Los AngelesCA90089 United States CREOL The College of Optics and Photonics University of Central Florida OrlandoFL32816 United States

Most acousto-optic lenses produce energy dissipating annular fringes. Here, we report a 3D dynamic focusing with fully-localized focus and 477-fold beam confinement with an extended depth of field (DoF) of more than 2...

ISBN: (纸本)9781557528209

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Cantilever Actuator Capsule for Magnetically Triggered Drug Delivery in the GI Tract

Cantilever Actuator Capsule for Magnetically Triggered Drug ...

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IEEE SENSORS

作者： Joshua A. Levy Michael A. Straker Luke A. Beardslee Reza Ghodssi Department of Materials Science and Engineering University of Maryland College Park Maryland USA Institute for Systems Research University of Maryland College Park Maryland USA Robert E. Fischell Institute for Biomedical Devices University of Maryland College Park Maryland USA Fischell Department of Bioengineering University of Maryland College Park Maryland USA Department of Electrical and Computer Engineering University of Maryland College Park Maryland USA

In this research, we present the development of a simple reed switch enabled magnetically triggerable electronic actuation system for protection and localized delivery of drugs in the intestinal tract. This system relies on polymeric cantilevers that can be multiplexed and released on command by melting the adhesive that holds them in compression. These cantilevers are conformally wrapped around the capsule and hold drug-loaded microneedles that penetrate the intestinal tissue to release drugs when deployed. We demonstrate the assembly, modeling, mechanical characterization, and deployment of this actuation capsule. COMSOL analysis suggested cantilever thickness of 254 $\mu\mathrm{m}$ is ideal to achieve the desired actuation force. This result was corroborated by mechanical experiments, and deployment was achieved using a handheld magnet in 2.3 seconds. Overall, this system provides the potential for targeted drug delivery in the GI tract, improving drug efficacy while minimizing side effects.

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Alignment of Tractography Streamlines using Deformation Transfer via Parallel Transport

arXiv

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arXiv 2021年

作者： Lizarraga, Andrew Lee, David Kubicki, Antoni Sahib, Ashish Nunez, Elvis Narr, Katherine Joshi, Shantanu H. Ahmanson Lovelace Brain Mapping Center Department of Neurology UCLA Department of Electrical and Computer Engineering UCLA Department of Bioengineering UCLA Department of Psychiatry and Behavioral Sciences UCLA

We present a geometric framework for aligning white matter fiber tracts. By registering fiber tracts between brains, one expects to see overlap of anatomical structures that often provide meaningful comparisons across subjects. However, the geometry of white matter tracts is highly heterogeneous, and finding direct tract-correspondence across multiple individuals remains a challenging problem. We present a novel deformation metric between tracts that allows one to compare tracts while simultaneously obtaining a registration. To accomplish this, fiber tracts are represented by an intrinsic mean along with the deformation fields represented by tangent vectors from the mean. In this setting, one can determine a parallel transport between tracts and then register corresponding tangent vectors. We present the results of bundle alignment on a population of 43 healthy adult subjects. © 2021, CC BY-NC-ND.

关键词： Deformation

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