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Priming with specific context improves large language model performance on nuclear cardiology board preparation test

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Journal of nuclear cardiology : official publication of the American Society of Nuclear Cardiology 2025年 102269页

作者： Waseem Hijazi Valerie Builoff Aditya Killekar Aakash Shanbhag Robert Jh Miller Damini Dey Joanna X Liang Kathleen Flood Daniel Berman Jamieson M Bourque Lawrence M Phillips Panithaya Chareonthaitawee Piotr J Slomka Departments of Medicine (Division of Artificial Intelligence in Medicine) Imaging and Biomedical Sciences Cedars-Sinai Medical Center Los Angeles CA USA. Departments of Medicine (Division of Artificial Intelligence in Medicine) Imaging and Biomedical Sciences Cedars-Sinai Medical Center Los Angeles CA USA Signal and Image Processing Institute Ming Hsieh Department of Electrical and Computer Engineering University of Southern California Los Angeles CA USA. Department of Cardiac Sciences University of Calgary Calgary AB Canada. American Society of Nuclear Cardiology Fairfax Virginia USA. Division of Cardiovascular Medicine and Radiology University of Virginia Health System Charlottesville VA USA. Leon H. Charney Division of Cardiology Department of Medicine NYU Grossman School of Medicine New York NY USA. Department of Cardiovascular Medicine Mayo Clinic Rochester MN USA. Departments of Medicine (Division of Artificial Intelligence in Medicine) Imaging and Biomedical Sciences Cedars-Sinai Medical Center Los Angeles CA USA. Electronic address: Piotr.Slomka@***.

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OEDIPUS: An experiment design framework for sparsity-constrained MRI

arXiv

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arXiv 2018年

作者： Haldar, Justin P. Kim, Daeun Signal and Image Processing Institute Ming Hsieh Department of Electrical Engineering University of Southern California Los AngelesCA90089 United States

This paper introduces a new estimation-theoretic framework for experiment design in the context of MR image reconstruction under sparsity constraints. The new framework is called OEDIPUS (Oracle-based Experiment Design for Imaging Parsimoniously Under Sparsity constraints), and is based on combining the constrained Cramér-Rao bound with classical experiment design techniques. Compared to popular random sampling approaches, OEDIPUS is fully deterministic and automatically tailors the sampling pattern to the specific imaging context of interest (i.e., accounting for coil geometry, anatomy, image contrast, etc.). OEDIPUS-based experiment designs are evaluated using retrospectively subsampled in vivo MRI data in several different contexts. Results demonstrate that OEDIPUSbased experiment designs have some desirable characteristics relative to conventional MRI sampling approaches. Copyright © 2018, The Authors. All rights reserved.

关键词： Magnetic resonance imaging

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A JND-based video quality assessment model and its application

arXiv

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arXiv 2018年

作者： Wang, Haiqiang Zhang, Xinfeng Yang, Chao Jay Kuo, C.-C. Ming-Hsieh Department of Electrical Engineering Signal and Image Processing Institute University of Southern California Los AngelesCA90089 United States

Based on the Just-Noticeable-Difference (JND) criterion, a subjective video quality assessment (VQA) dataset, called the VideoSet, was constructed recently. In this work, we propose a JND-based VQA model using a probabilistic framework to analyze and clean collected subjective test data. While most traditional VQA models focus on content variability, our proposed VQA model takes both subject and content variabilities into account. The model parameters used to describe subject and content variabilities are jointly optimized by solving a maximum likelihood estimation (MLE) problem. As an application, the new subjective VQA model is used to filter out unreliable video quality scores collected in the VideoSet. Experiments are conducted to demonstrate the effectiveness of the proposed model. Copyright © 2018, The Authors. All rights reserved.

关键词： Maximum likelihood estimation

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Introducing Enumerative Sphere Shaping for Optical Communication systems with Short Blocklengths

arXiv

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arXiv 2019年

作者： Amari, Abdelkerim Goossens, Sebastiaan Gültekin, Yunus Can Vassilieva, Olga Kim, Inwoong Ikeuchi, Tadashi Okonkwo, Chigo Willems, Frans M.J. Alvarado, Alex Information and Communication Theory Lab Signal Processing Systems Group Department of Electrical Engineering Eindhoven University of Technology Eindhoven5600 MB Netherlands Institute for Photonic Integration Eindhoven University of Technology Eindhoven5600 MB Netherlands Fujitsu Laboratories of America Inc. RichardsonTX75082 United States

—Probabilistic shaping based on constant composition distribution matching (CCDM) has received considerable attention as a way to increase the capacity of fiber optical communication systems. CCDM suffers from significant rate loss at short blocklengths and requires long blocklengths to achieve high shaping gain, which makes its implementation very challenging. In this paper, we propose to use enumerative sphere shaping (ESS) and investigate its performance for the nonlinear fiber optical channel. ESS has lower rate loss than CCDM at the same shaping rate, which makes it a suitable candidate to be implemented in real-time high-speed optical systems. In this paper, we first show that finite blocklength ESS and CCDM exhibit higher effective signal-to-noise ratio than their infinite blocklength counterparts. These results show that for the nonlinear fiber optical channel, large blocklengths should be avoided. We then show that for a 400 Gb/s dual-polarization 64-QAM WDM transmission system, ESS with short blocklengths outperforms both uniform signaling and CCDM. Gains in terms of both bit-metric decoding rate and bit-error rate are presented. ESS with a blocklength of 200 is shown to provide an extension reach of about 200 km in comparison with CCDM with the same blocklength. The obtained reach increase of ESS with a blocklength of 200 over uniform signaling is approximately 450 km (approximately 19%). Copyright © 2019, The Authors. All rights reserved.

关键词： signal to noise ratio

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Detection of Fusarium wilt on Phalaenopsis stem base region using band selection techniques 38

Detection of Fusarium wilt on Phalaenopsis stem base region ...

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38th Annual IEEE International Geoscience and Remote Sensing Symposium, IGARSS 2018

作者： Lee, Meng-Chueh Ma, Kenneth-Yeonkong Ouyang, Yen-Chieh Ou-Yang, Mang Guo, Horng-Yuh Liu, Tsang-Sen Chen, Hsian-Min Wu, Chao-Cheng Chang, Chgein-I Department of Communications Engineering National Chung Hsing University Taichung Taiwan Department of Electrical Engineering National Chung Hsing University Taichung Taiwan National Chiao-Tung University Department of Electrical and Computer Engineering Hsinchu City Taiwan Taiwan Agriculture Research Institute Nan-Tou Taiwan Center for Quantitative Imaging in Medicine Taichung Veterans General Hospital Taichung Taiwan Department of Electrical Engineering National Taipei University of Technology Taipei Taiwan Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County BaltimoreMD21250 United States

ISBN: (纸本)9781538671504

Phalaenopsis is a significant agriculture product with high economic value in Taiwan. However, the fusarium wilt causes Phalaenopsis leaves turning yellow, thinning, water loss, and finally died. This paper presents an emerging method to detect fusarium wilt on Phalaenopsis stem base. In order to build the detection models, the hyperspectral databases are generated form two statues of Phalaenopsis samples, which are health and disease sample. We applied band selection (BS) processing base on band prioritization (BP) and band de-correlation (BD) to extract the significant bands and eliminate the redundant bands. Then, three algorithms were used, orthogonal subspace projection (OSP), constrain energy minimization (CEM), and support vector machine (SVM) to detect the fusarium wilt. © 2018 IEEE

关键词： Diseases Hyperspectral imaging Support vector machines Agriculture Databases Entropy

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Glaucoma Screening Through Level Set for Optic Disc Segmentation and Textural Features for Classification

Glaucoma Screening Through Level Set for Optic Disc Segmenta...

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International Conference on Intelligent and Advanced systems, ICIAS

作者： Apurv Joshi Atharva Kadethankar Vedant Patwardhan Prasanna Porwal Samiksha Pachade Manesh Kokare Fabrice Meriaudeau Center of Excellence in Signal and Image Processing Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India Department of Electrical & Electronic Engineering University Teknologi PETRONAS Malaysia

Glaucoma is considered as world's second biggest health emergency of this century. Glaucoma is an irremediable chronic ocular disease. In Glaucoma, Optic Nerve Head (ONH) gets damaged due to loss of ganglion cells. This damage of ONH causes cupping of nerve head and optic cup size increases with respect to the size of optic disc. These changes in ONH can be detected using various image processing methods which can be applied on retinal images acquired using Optical Coherence Tomograph, Retinal fundus camera and Heidelberg Retina Tomograph. This paper proposes an approach to detect Glaucoma automatically from retinal fundus images. A level set based approach for segmentation of optic disc (OD) is used and further analysis of segmented OD is done by textural information. In this approach, image features are obtained by the use of Local Binary Pattern (LBP) and these image features were classified using Support Vector Machine(SVM) classifier.

关键词： Level set Optical imaging image segmentation Feature extraction Retina Integrated optics Adaptive optics

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Automatic Segmentation of Optic Disc by Gradient Minimization Based Approach

Automatic Segmentation of Optic Disc by Gradient Minimizatio...

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International Conference on Intelligent and Advanced systems, ICIAS

作者： Prasanna Porwal Samiksha Pachade Atharva Kadethankar Apurv Joshi Vedant Patwardhan Ravi Kamble Manesh Kokare Fabrice Meriaudeau Center of Excellence in Signal and Image Processing Shri Guru Gobind Singhji Institute of Engineering and Technology Nanded India Department of Electrical & Electronic Engineering University Teknologi PETRONAS Malaysia

Diabetic Retinopathy (DR) and Glaucoma are the eye diseases that cause progressive damage to patient's vision over time. Optic disc detection and segmentation is of significant importance for automating the screening of both diseases. The method proposed for the precise and fast segmentation of the optic disc mainly based obtaining optic disc center location using intensity profile analysis and further segmentation of chosen region of interest using L 0 gradient minimization based technique. The optimum threshold was chosen for OD segmentation using Otsu's method. Performance of the technique is evaluated using Dice and Jaccard metrics that are obtained as 80.23% and 71.17% 78.46% and 82.63% respectively on IDRiD and the MESSIDOR dataset. The proposed method is found to be very fast and efficient.

关键词： Optical imaging image segmentation Adaptive optics Minimization Retina Optical distortion Retinopathy

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Computer vision-based apple grading for golden delicious apples based on surface features

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Information processing in Agriculture 2017年第1期4卷 33-40页

作者： Payman Moallem Alireza Serajoddin Hossein Pourghassem Department of Electrical Engineering Faculty of EngineeringUniversity of IsfahanHezarjerib StreetIsfahanIran Applied Image and Signal Processing Research Group Research Center for Signal Processing and Intelligent SystemsUniversity of IsfahanHezarjerib StreetIsfahanIran Department of Electrical Engineering Najafabad BranchIslamic Azad UniversityNajafabadIsfahanIrand Digital Processing and Machine Vision Research Center Najafabad BranchIslamic Azad UniversityNajafabadIran

In this paper,a computer vision-based algorithm for golden delicious apple grading is proposed which works in six ***-apple pixels as background are firstly removed from input ***,stem end is detected by combination of morphological methods and Mahalanobis distant *** region is also detected by applying K-means clustering on the Cb component in YCbCr color *** that,defects segmentation is achieved using Multi-Layer Perceptron(MLP)neural *** the next step,stem end and calyx regions are removed from defected regions to refine and improve apple grading ***,statistical,textural and geometric features from refined defected regions are ***,for apple grading,a comparison between performance of Support Vector Machine(SVM),MLP and K-Nearest Neighbor(KNN)classifiers is *** is done in two manners which in the first one,an input apple is classified into two categories of healthy and *** the second manner,the input apple is classified into three categories of first rank,second rank and rejected *** both grading steps,SVM classifier works as the best one with recognition rate of 92.5%and 89.2%for two categories(healthy and defected)and three quality categories(first rank,second rank and rejected ones),among 120 different golden delicious apple images,respectively,considering K-folding with K=***,the accuracy of the proposed segmentation algorithms including stem end detection and calyx detection are evaluated for two different apple image databases.

关键词： Golden delicious apple Grading Computer vision Segmentation Classification

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A Rate-Distortion Approach to Caching

A Rate-Distortion Approach to Caching

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作者： Timo, Roy Bidokhti, Shirin Saeedi Wigger, Michele Geiger, Bernhard C. Ericsson ResearchTorshamnsgatan Stockholm23164 80 Sweden Department of Electrical Engineering Stanford University StanfordCA94305 United States Department of Electrical and Systems Engineering University of Pennsylvania PhiladelphiaPA19104 United States Communications and Electronics Department Telecom ParisTech Paris75634 France Institute for Communications Engineering Technical University of Munich Munich80333 Germany Signal Processing and Speech Communication Laboratory Graz University of Technology Graz8010 Austria

In this paper, we consider a lossy single-user caching problem with correlated sources. We first describe the fundamental interplay between the source correlations, the capacity of the user's cache, the user's reconstruction distortion requirements, and the final delivery-phase (compression) rate. We then illustrate this interplay using a multivariate Gaussian source example and a binary symmetric source example. To fully explore the effect of the user's distortion requirements, we formulate the caching problem using f-separable distortion functions recently introduce by Shkel and Verdú. The class of f-separable distortion functions includes separable distortion functions as a special case, and our analysis covers both the expected-and excess-distortion settings in detail. We also determine what 'common information' should be placed in the cache, and what information should be transmitted during the delivery phase. To this end, two new common-information measures are introduced for caching, and their relationship to the common-information measures of Wyner, Gács, and Körner is discussed in detail. © 1963-2012 IEEE.

关键词： signal distortion

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Self-Awareness for Autonomous systems

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PROCEEDINGS OF THE IEEE 2020年第7期108卷 971-975页

作者： Dutt, Nikil Regazzoni, Carlo S. Rinner, Bernhard Yao, Xin Nikil Dutt (Fellow IEEE) received the Ph.D. degree from the University of Illinois at Urbana–Champaign Champaign IL USA in 1989.""He is currently a Distinguished Professor of computer science (CS) cognitive sciences and electrical engineering and computer sciences (EECS) with the University of California at Irvine Irvine CA USA. He is a coauthor of seven books. His research interests include embedded systems electronic design automation (EDA) computer architecture distributed systems healthcare Internet of Things (IoT) and brain-inspired architectures and computing.""Dr. Dutt is a Fellow of ACM. He was a recipient of the IFIP Silver Core Award. He has received numerous best paper awards. He serves as the Steering Committee Chair of the IEEE/ACM Embedded Systems Week (ESWEEK). He is also on the steering organizing and program committees of several premier EDA and embedded system design conferences and workshops. He has served on the Editorial Boards for the IEEE Transactions on Very Large Scale Integration (VLSI) Systems and the ACM Transactions on Embedded Computing Systems and also previously served as the Editor-in-Chief (EiC) for the ACM Transactions on Design Automation of Electronic Systems. He served on the Advisory Boards of the IEEE Embedded Systems Letters the ACM Special Interest Group on Embedded Systems the ACM Special Interest Group on Design Automationt and the ACM Transactions on Embedded Computing Systems. Carlo S. Regazzoni (Senior Member IEEE) received the M.S. and Ph.D. degrees in electronic and telecommunications engineering from the University of Genoa Genoa Italy in 1987 and 1992 respectively.""He is currently a Full Professor of cognitive telecommunications systems with the Department of Electrical Electronics and Telecommunication Engineering and Naval Architecture (DITEN) University of Genoa and a Co-Ordinator of the Joint Doctorate on Interactive and Cognitive Environments (JDICE) international Ph.D. course started initially as EU Erasmus Mundus Project and

Autonomous systems are able to make decisions and potentially take actions without direct human intervention, which requires some knowledge about the system and its environment as well as goal-oriented reasoning. In computer systems, one can derive such behavior from the concept of a rational agent with autonomy (“control over its own actions”), reactivity (“react to events from the environment”), proactivity (“act on its own initiative”), and sociality (“interact with other agents”) as fundamental properties \n[1]\n. Autonomous systems will undoubtedly pervade into our everyday lives, and we will find them in a variety of domains and applications including robotics, transportation, health care, communications, and entertainment to name a few. \nThe articles in this month’s special issue cover concepts and fundamentals, architectures and techniques, and applications and case studies in the exciting area of self-awareness in autonomous systems.

关键词： Special issues and sections Autonomous systems Self-aware Robot sensing systems Computational modeling

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