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arXiv 2025年

作者： Imran, Muhammad Krebs, Jonathan R. Sivaraman, Vishal Balaji Zhang, Teng Kumar, Amarjeet Ueland, Walker R. Fassler, Michael J. Huang, Jinlong Sun, Xiao Wang, Lisheng Shi, Pengcheng Rokuss, Maximilian Baumgartner, Michael Kirchhof, Yannick Maier-Hein, Klaus H. Isensee, Fabian Liu, Shuolin Han, Bing Nguyen, Bong Thanh Shin, Dong-Jin Ji-Woo, Park Choi, Mathew Uhm, Kwang-Hyun Ko, Sung-Jea Lee, Chanwoong Chun, Jaehee Kim, Jin Sung Zhang, Minghui Zhang, Hanxiao You, Xin Gu, Yun Pan, Zhaohong Liu, Xuan Liang, Xiaokun Tiefenthaler, Markus Almar-Munoz, Enrique Schwab, Matthias Kotyushev, Mikhail Epifanov, Rostislav Wodzinski, Marek Müller, Henning Qayyum, Abdul Mazher, Moona Niederer, Steven A. Wang, Zhiwei Yang, Kaixiang Ren, Jintao Korreman, Stine Sofia Gao, Yuchong Zeng, Hongye Zheng, Haoyu Zheng, Rui Yue, Jinghua Zhou, Fugen Liu, Bo Cosman, Alexander Liang, Muxuan Zhao, Chang Upchurch, Gilbert R. Ma, Jun Zhou, Yuyin Cooper, Michol A. Shao, Wei Department of Medicine University of Florida GainesvilleFL32611 United States Department of Surgery University of Florida GainesvilleFL32611 United States Department of Electrical and Computer Engineering University of Florida GainesvilleFL32611 United States Department of Computer Information Science and Engineering University of Florida GainesvilleFL32611 United States Shanghai Jiao Tong University Shanghai China Electronic & Information Engineering School Harbin Institute of Technology [Shenzhen Shenzhen China Division of Medical Image Computing German Cancer Research Center [DKFZ Heidelberg Germany CO. LTD Beijing China MedAI Seoul Korea Republic of Korea University Seoul Korea Republic of Department of Radiation Oncology Yonsei Cancer Center Heavy Ion Therapy Research Institute Yonsei University College of Medicine Seoul Korea Republic of Institute of Medical Robotics Shanghai Jiao Tong University Shanghai China Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen518055 China Medical University of Innsbruck Innsbruck Austria Novosibirsk State University Novosibirsk Russia AGH University of Krakow Krakow Poland Sierre Switzerland University of Geneva Geneva Switzerland The Sense Innovation and Research Center Sion Switzerland National Heart and Lung Institute Faculty of Medicine Imperial College London London United Kingdom Wuhan National Laboratory for Optoelectronics Huazhong University of Science and Technology Hubei Wuhan China Aarhus University Department of Clinical Medicine Nordre Palle Juul-Jensens Blvd. 11 Aarhus8200 Denmark Shanghaitech University Pudong Shanghai China Image Processing Center Beihang University Beijing China Department of Computer Science and Engineering University of California Santa CruzCA95064 United States Department of Biostatistics University of Florida GainesvilleFL32611 United States University Health Network ON Canada Agronomy Department University of F

Multi-class segmentation of the aorta in computed tomography angiography (CTA) scans is essential for diagnosing and planning complex endovascular treatments for patients with aortic dissections. However, existing methods reduce aortic segmentation to a binary problem, limiting their ability to measure diameters across different branches and zones. Furthermore, no open-source dataset is currently available to support the development of multi-class aortic segmentation methods. To address this gap, we organized the AortaSeg24 MICCAI Challenge, introducing the first dataset of 100 CTA volumes annotated for 23 clinically relevant aortic branches and zones. This dataset was designed to facilitate both model development and validation. The challenge attracted 121 teams worldwide, with participants leveraging state-of-the-art frameworks such as nnU-Net and exploring novel techniques, including cascaded models, data augmentation strategies, and custom loss functions. We evaluated the submitted algorithms using the Dice Similarity Coefficient (DSC) and Normalized Surface Distance (NSD), highlighting the approaches adopted by the top five performing teams. This paper presents the challenge design, dataset details, evaluation metrics, and an in-depth analysis of the top-performing algorithms. The annotated dataset, evaluation code, and implementations of the leading methods are publicly available to support further research. All resources can be accessed at https://***. © 2025, CC BY-NC-SA.

关键词： computerized tomography

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PerSIM: MULTI-RESOLUTION image QUALITY ASSESSMENT IN THE PERCEPTUALLY UNIFORM COLOR DOMAIN

PerSIM: MULTI-RESOLUTION IMAGE QUALITY ASSESSMENT IN THE PER...

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IEEE International Conference on image processing

作者： Dogancan Temel Ghassan AlRegib Center for Signal and Information Processing (CSIP) School of Electrical and Computer Engineering Georgia Institute of Technology

ISBN: (纸本)9781479983407

An average observer perceives the world in color instead of black and white. Moreover, the visual system focuses on structures and segments instead of individual pixels. Based on these observations, we propose a full reference objective image quality metric modeling visual system characteristics and chroma similarity in the perceptually uniform color domain (Lab). Laplacian of Gaussian features are obtained in the L channel to model the retinal ganglion cells in human visual system and color similarity is calculated over the a and b channels. In the proposed perceptual similarity index (PerSIM), a multi-resolution approach is followed to mimic the hierarchical nature of human visual system. LIVE and TID2013 databases are used in the validation and PerSIM outperforms all the compared metrics in the overall databases in terms of ranking, monotonic behavior and linearity.

关键词： image quality analysis Human visual system Perception LoG features Similarity index image quality analysis Visual System Species diversity senses Perception Color image quality Uniforms Database

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Spectral derivative feature coding for hyperspectral signature analysis

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Pattern Recognition 2009年第3期42卷 395-408页

作者： Chang, Chein-I Chakravarty, Sumit Chen, Hsian-Min Ouyang, Yen-Chieh Remote Sensing Signal and Image Processing Laboratory Department of Computer Science and Electrical Engineering University of Maryland Baltimore County Baltimore MD 21250 United States Department of Electrical Engineering National Chung Hsing University Taichung Taiwan Environmental Restoration and Disaster Reduction Research Center National Chung Hsing University Taichung Taiwan Department of Medical Research China Medical University Hospital Taichung Taiwan Department of Radiology China Medical University Hospital Taichung Taiwan

This paper presents a new approach to hyperspectral signature analysis, called spectral derivative feature coding (SDFC). It is derived from texture features used in texture classification to dictate gradient changes among adjacent bands in characterizing spectral variations so as to improve better spectral discrimination and classification. In order to evaluate its performance, two known binary coding methods, spectral analysis manager (SPAM) and spectral feature-based binary coding (SFBC) are used to conduct comparative analysis. Experimental results demonstrate that the proposed SDFC performs more effectively in capturing spectral characteristics than do SPAM and SFBC. © 2008 Elsevier Ltd. All rights reserved.

关键词： Spectrum analysis

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Effective supervised classification of fMRI activation maps between populations by spatial descriptors

Effective supervised classification of fMRI activation maps ...

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2011 7th Iranian Conference on Machine Vision and image processing, MVIP 2011

作者： Eshaghian, Shaghayegh Hossein-Zadeh, Gholam-Ali Soltanian-Zadeh, Hamid Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran 14395-515 Iran Image Analysis Laboratory Radiology Department Henry Ford Hospital Detroit MI 48202 United States

ISBN: (纸本)9781457715358

The major obstacle in discrimination between different groups of subjects in a common cognitive state, by functional Magnetic Resonance Imaging (fMRI), has been the high intersubject functional and anatomical variability in the spatial patterns of brain activity. To overcome this, we have used two types of spatial descriptors that characterize the brain regions of interest (ROIs) involved in the cognitive tasks. They include, firstly three-dimensional invariant moment descriptors (3-DMIs), and secondly k-dimensional feature vectors based on concentric spheres. Both types of descriptors are applied to analyze the spatial patterns of cognitive activity of a challenging task and then to classify them across two different subject groups. SVM classifiers along with sequential floating forward feature selection technique are applied to the extracted descriptors of each ROI across the subjects. Our method is applied to experimental fMRI data with the aim of discriminating mental status of heroin IV (Intravenous) abusers and from of those in control subjects in a visual cue task which can induce drug craving. Our results demonstrate that 3-D texture of activation maps provide a good discrimination (with high accuracy) between healthy and addict group. © 2011 IEEE.

关键词： Brain

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REDUCED-REFERENCE PERCEPTUAL QUALITY ASSESSMENT FOR VIDEO STREAMING

REDUCED-REFERENCE PERCEPTUAL QUALITY ASSESSMENT FOR VIDEO ST...

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IEEE International Conference on image processing

作者： Mohammed A. Aabed Ghassan AlRegib Center for Signal and Information Processing (CSIP) School of Electrical and Computer Engineering Georgia Institute of Technology

ISBN: (纸本)9781479983407

We propose a perceptual video quality monitoring metric for streaming applications using the optical flow features. This approach is a reduced-reference pixel-based and relies only on the deviation of the optical flow of the corrupted frames. This techniques compares an optical flow descriptor from the corrupted frame against the descriptor obtained from the anchor frame. This approach is suitable for videos with complex motion patterns. Our technique does not make any assumptions on the coding conditions, network loss patterns or error concealment techniques. We validate our proposed metric by testing it on a variety of distorted sequences from the LIVE mobile database. Our results show that our metric estimates the perceptual quality at the sequence level accurately. We report the correlation coefficients with the differential mean opinion scores (DMOS) reported in the database. The results show Spearman's correlations of 0.88 for the tested sequences.

关键词： Video quality monitoring Channel distortion Video streaming HEVC H.264/MPEG-4 AVC Optical flow Network losses Optic Flow Video streaming network losses Videotapes High efficiency video coding channel distortion Quality assessment patterning of movement

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Universal image steganalysis against spatial-domain steganography based on energy distribution of singular values

Universal image steganalysis against spatial-domain steganog...

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7th International Conference on Information Technology and Application, ICITA 2011

作者： Shojaei-Hashemi, Anahita Soltanian-Zadeh, Hamid Ghaemmagham, Shahrokh Kamarei, Mahmoud School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States Electronics Research Institute Sharif University of Technology Tehran Iran

ISBN: (纸本)9780980326741

A passive image steganalysis method is proposed to universally detect spatial-domain steganography schemes. It is shown to have better performance than universal steganalyzers known to be powerful in spatial domain, including the WFLogSv and the WAM methods. This level of accuracy is the result of improving the WFLogSv steganalyzer by considering a more comprehensive relationship between the singular values of each image block and the linear correlation of the rows and the columns. That is, instead of the closeness of the lower singular values to zero, the energy distribution of the singular values is investigated. An innovative measure is proposed for this investigation, which is inspired from arithmetic mean-geometric mean inequality. Experimental results confirm the supremacy of the proposed steganalysis scheme over its counterparts.

关键词： Singular value decomposition

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Universal steganalysis based on local prediction error in wavelet domain

Universal steganalysis based on local prediction error in wa...

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7th International Conference on Intelligent Information Hiding and Multimedia signal processing, IIHMSP 2011

作者： Shojaei-Hashemi, Anahita Mehdipour-Ghazi, Mostafa Ghaemmaghami, Shahrokh Soltanian-Zadeh, Hamid School of Electrical and Computer Engineering College of Engineering University of Tehran Tehran Iran Electronics Research Institute Sharif University of Technology Tehran Iran Control and Intelligent Processing Center of Excellence School of Electrical and Computer Engineering University of Tehran Tehran Iran Image Analysis Laboratory Department of Radiology Henry Ford Health System Detroit MI United States

ISBN: (纸本)9780769545172

A passive universal image steganalysis method is proposed that is shown to be of higher detection accuracy than existing truly blind steganalysis methods including Farid's and the WAM. This is achieved by improving some weaknesses of Farid's steganalysis scheme in feature extraction, that is, instead of deriving an over-determined equation system for each sub band of the wavelet decomposition, the sub bands are divided into overlapping blocks and an over-determined equation system is constructed for each block. To guarantee the existence of finite answers, the over-determined equation systems are solved in a way different from Farid's by using Moore-Penrose pseudo-inverse concept. Further improvement to the performance is achieved by adding diagonal directions and increasing the number of moments. The comparative evaluations confirm the superiority of the proposed method over prevalent blind steganalysis schemes. © 2011 IEEE.

关键词： Wavelet decomposition

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Expectation propagation approach to joint channel estimation and decoding for OFDM systems

Expectation propagation approach to joint channel estimation...

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2014 IEEE International Conference on Acoustics, Speech, and signal processing, ICASSP 2014

作者： Wu, Sheng Kuang, Linling Ni, Zuyao Lu, Jianhua Huang, Defeng David Guo, Qinghua Department of Electronic Engineering Tsinghua University China Tsinghua Space Center Tsinghua University China Research Institute of Information Technology Tsinghua University China Shenzhen Key Laboratory of Wireless Broadband Communication and Signal Processing China School of Electrical Electronic and Computer Engineering University of Western Australia Australia School of Electrical Computer and Telecommunications Engineering University of Wollongong Australia

ISBN: (纸本)9781479928927

We propose a message-passing algorithm of joint channel estimation and decoding for OFDM systems, where expectation propagation is exploited to deal with channel estimation. Specially, the message updating is formulated into a recursive form. As a result, for system with K subcarriers and L channel taps, only O(K + L) messages need to be tracked, and meanwhile they can be efficiently calculated using FFT with complexity O(K-A- + K log2 K), where -A- denotes the constellation size. Numerical experiments show that our algorithm achieves BER performance within 0.5 dB of the known-channel bound. © 2014 IEEE.

关键词： Orthogonal frequency division multiplexing

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Minutiae Triangle Graphs: A New Fingerprint Representation with Invariance Properties

Minutiae Triangle Graphs: A New Fingerprint Representation w...

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International Conference on image and Vision Computing New Zealand, IVCNZ

作者： Akmal-Jahan Mohamed-Abdul-Cader Watcharapong Chaidee Jasmine Banks Vinod Chandran Vision and Signal Processing Lab School of Electrical Engineering and Computer Science Queensland University of Technology Brisbane Australia Signal and Image Processing Laboratory Kasetsart University Bangkok Thailand

A new algorithm for matching finger or palm prints is presented for use where the full hand is considered as a biometric and only parts may be available in images for comparison. The algorithm uses an extended version of the minutiae-based approach treating the pattern as a graph of minutiae-like points. The procedure to identify minutiae-like points uses Gabor filtering, edge detection and thinning and following line patterns. A set of such points is subjected to Delaunay triangulation yielding a starting set of base-triangles for matching. There can be multiple matches of such triangles between the template and test - as similar triangles with a tolerance in the angles. Graphs are then grown to 5 and more nodes as long as a match can be found, until the maximum size matching graph is obtained. If the test matches a significant part of the template, the maximum order of graph matched will be high. The matching process is robust to transformations such as rotation, translation and scale changes. It can be applied to any part of the hand provided minutiae-like points are identifiable prior to the matching steps. The algorithm is tested using 158 fingerprint images from FVC 2002 DB1. 100 genuine and 5048 impostor scores are generated from 46 templates and 112 testing images. It had an EER of about 6%. It proves the principle behind the methodology and demonstrates that the method can be effective with degraded fingerprint images and is robust to similarity transformations present in the data. It can be applied for forensic fingerprint matching from the palm or parts other than the fingertips. By using multiple parts and multiple templates, the accuracy of the method will be improved with fusion in future versions of the algorithm.

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A wavelet based stereo image coding algorithm

A wavelet based stereo image coding algorithm

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International Conference on Acoustics, Speech, and signal processing (ICASSP)

作者： Qin Jiang Joon Jae Lee M.H. Hayes Center for Signal and Image Processing School of Electrical & Computer Engineering Georgia Institute of Technology Atlanta GA USA Department of Computer Engineering Dong Seo University busan South Korea

Stereo image pair coding is an important issue in stereo data compression. A wavelet based stereo image pair coding algorithm is proposed in this paper. The wavelet transform is used to decompose the image into an approximation image and three edge images. In the wavelet domain, a disparity estimation technique is developed to estimate the disparity field using both approximation image and edge images. To improve the accuracy of estimation of wavelet images produced by the disparity compensation technique, a novel wavelet based subspace projection technique (SPT) is developed. In the SPT, the block dependent subspaces are constructed using block varying basis vectors that are derived from the disparity compensated wavelet images. Experimental results show that the proposed algorithm is efficient to achieve stereo image compression.

关键词： image coding Wavelet domain Wavelet transforms Layout image storage Decoding Wavelet analysis signal processing image processing Data compression

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