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Semi-Supervised and Self-Supervised Collaborative Learning for Prostate 3D MR Image Segmentation

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Semi-Supervised and Self-Supervised Collaborative Learning f...

IEEE International Symposium on Biomedical Imaging

作者： Yousuf Babiker M. Osman Cheng Li Weijian Huang Nazik Elsayed Leslie Ying Hairong Zheng Shanshan Wang Paul C. Lauterbur Research Center for Biomedical Imaging Shenzhen Institute of Advanced Technology Chinese Academy of Sciences Shenzhen China University of Chinese Academy of Sciences Beijing China Faculty of Mathematical and Computer Sciences University of Gezira Wad Madani Sudan Department of Biomedical Engineering and Department of Electrical Engineering University at Buffalo The State University of New York New York USA Guangdong Provincial Key Laboratory of Artificial Intelligence in Medical Image Analysis and Application Guangdong China

Volumetric magnetic resonance (MR) image segmentation plays an important role in many clinical applications. Deep learning (DL) has recently achieved state-of-the-art or even human-level performance on various image segmentation tasks. Nevertheless, manually annotating volumetric MR images for DL model training is labor-exhaustive and time-consuming. In this work, we aim to train a semi-supervised and self-supervised collaborative learning framework for prostate 3D MR image segmentation while using extremely sparse annotations, for which the ground truth annotations are provided for just the central slice of each volumetric MR image. Specifically, semi-supervised learning and self-supervised learning methods are used to generate two independent sets of pseudo labels. These pseudo labels are then fused by the Boolean operation to extract a more confident pseudo label set. The images with either manual or network self-generated labels are then employed to train a segmentation model for target volume extraction. Experimental results on a publicly available prostate MR image dataset demonstrate that, while requiring significantly less annotation effort, our framework generates very encouraging segmentation results. The proposed framework is very useful in clinical applications when training data with dense annotations are difficult to obtain.

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Revisiting Test Cases to Boost Generate-and-Validate Program Repair

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Revisiting Test Cases to Boost Generate-and-Validate Program...

International Conference on Software Maintenance (ICSM)

作者： Jingtang Zhang Kui Liu Dongsun Kim Li Li Zhe Liu Jacques Klein Tegawendé F. Bissyandé Nanjing University of Aeronautics and Astronautics Nanjing China Key Laboratory of Safety-Critical Software (Nanjing University of Aeronautics and Astronautics) Nanjing China State Key Laboratory of Mathematical Engineering and Advanced Computing Wuxi China Kyungpook National University Daegu South Korea Monash University Melbourne Australia Interdisciplinary Centre for Security Reliability and Trust (SnT) University of Luxembourg Luxembourg

Fault localization produces bug positions as the basic input for many automated program repair (APR) systems. Given that test cases are the common means that automatic fault localization techniques leverage, we investigate the impact of their characteristics (in terms of quality and quantity) on APR. In particular, we analyze the statements that appear in crash stack traces when test cases fail (note that stack traces are available when an ordinary test case fails since its verdict is often made by assertions that produce errors such as AssertError in Java and JUnit), and explore the possibility of using some relevant crash information to enhance fault localization; this ultimately improves the effectiveness of APR tools. Our study reveals that the considered state-of-the-art APR systems achieve the best performance when fixing bugs associated with boolean type expected values (e.g., assertTrue ()) or assertFalse(). In contrast, they achieve their worst performance when addressing bugs related to null check assertions. Meanwhile, null check bugs as well as the bugs associated with boolean and string type expected values are still the main challenge that should be addressed by the future APR. For exception throwing bugs, existing APR systems present the best performance on fixing NullPointerException bugs, while the tough task of them is to resolve the bugs throwing developer-defined exceptions. The information in stack traces after executing the bug-triggering test cases can be used to effectively improve the performance on fault localization and program repair.

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Topologically protected edge states in time photonic crystals with chiral symmetry

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arXiv 2025年

作者： Yang, Yukun Hu, Hao Liu, Liangliang Yang, Yihao Yu, Youxiu Long, Yang Zheng, Xuezhi Luo, Yu Li, Zhuo Garcia-Vidal, Francisco J. National Key Laboratory of Microwave Photonics College of Electronic and Information Engineering Nanjing University of Aeronautics and Astronautics Nanjing211106 China State Key Laboratory of Extreme Photonics and Instrumentation ZJU-Hangzhou Global Scientific and Technological Innovation Center Zhejiang University Hangzhou310027 China International Joint Innovation Center The Electromagnetics Academy Zhejiang University Zhejiang University Haining314400 China Key Lab. of Advanced Micro/Nano Electronic Devices & Smart Systems of Zhejiang Jinhua Institute of Zhejiang University Zhejiang University Jinhua321099 China Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Department of Electrical Engineering KU Leuven Leuven3001 Belgium Universidad Autónoma de Madrid MadridE-28049 Spain

Time photonic crystals are media in which their electromagnetic parameters are modulated periodically in time, showing promising applications in non-resonant lasers and particle accelerators, among others. Traditionally utilized to study space photonic crystals, topological band theory has also been translated recently to analyze time photonic crystals with time inversion symmetry, enabling the construction of the temporal version of topological edge states. However, temporal disorder can readily break time inversion symmetry in practice, hence likely destroying the edge states associated with this type of time photonic crystals. To overcome this limitation, here we propose a new class of time photonic crystals presenting chiral symmetry instead, whose edge states exhibit superior robustness over the time-reversal-symmetry-protected counterparts. Our time photonic crystal is equivalent to a temporal version of the Su-Schrieffer-Heeger model, and the chiral symmetry of this type of time photonic crystals quantizes the winding number defined in the Bloch frequency band. Remarkably, random temporal disorders do not impact the eigenfrequencies of these chiral-symmetry-protected edge states, while instead enhancing their temporal localizations. Our findings thus provide a promising paradigm to control field amplification with exceptional robustness as well as being a feasible platform to investigate various topological phases in time-varying media. Copyright © 2025, The Authors. All rights reserved.

关键词： Topology

Optimization of performance of the KM2A full array using the Crab Nebula

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Chinese Physics C 2024年第6期48卷 169-178页

作者：曹臻 F.Aharonian 安琪阿西克古白云翔包逸炜 D.Bastieri 毕效军毕玉江蔡金庭曹晴曹文羽曹喆常进常劲帆陈尚明陈恩生陈亮陈林陈龙陈明君陈玛丽陈起辉陈素弘陈天禄陈阳程宁程耀东崔明阳崔树旺崔晓红崔昱东戴本忠代洪亮戴子高单增罗布 D.della Volpe 董绪强段凯凯樊军辉范一中方军方堃冯存峰封莉冯少辉丰晓婷冯有亮 S.Gabici 高博高川东高林青高启高卫高伟康葛茂茂耿利斯 G.Giacinti 龚光华苟全补顾旻皓郭福来郭晓磊郭义庆郭莹莹韩毅昂何会海贺昊宁何佳银何新波何钰 M.Heller 贺远强侯博文侯超侯贤胡红波胡铨胡世聪黄代绘黄天奇黄文俊黄性涛黄晓渊黄勇黄志成季筱璐贾焕玉贾康江琨姜晓巍姜泽军金敏康明铭柯通 D.Kuleshov.K.Kurinov 李兵兵李澄李骢李丹李飞李海波李会财李华阳李军李剑李捷李凯李文龙李文莲李秀荣李昕李一卓李哲黎卓梁恩维梁云峰林苏杰刘冰刘成刘栋刘虎刘海东刘佳刘江来刘金艳刘茂元柳若愚刘四明刘伟刘怡刘以农鲁睿罗晴吕洪魁马伯强马玲玲马欣华毛基荣闵振 W.Mitthumsiri 穆慧君南云程 A.Neronov 区子维庞彬宇 P.Pattarakijwanich 裴致远齐孟尧祁业情乔冰强秦家军 D.Ruffolo A.Sáiz D.Semikoz 邵澄宇邵琅 O.Shchegolev 盛祥东舒富文宋慧超 Yu.V.Stenkin V.Stepanov 苏扬孙秦宁孙晓娜孙志斌谭柏轩唐庆文唐泽波田文武王超王昌贝王广威王洪光王惠惠王建成汪凯王利苹王玲玉王培汉王冉王为王祥高王祥玉王阳王玉东王岩谨王忠海王仲翔王振王铮韦大明魏俊杰魏永健文韬吴超勇吴含荣武莎吴雪峰吴雨生席邵强夏捷夏君集项光漫肖迪泫肖刚辛广广辛玉良邢祎熊峥徐东莲徐仁峰徐仁新徐伟立薛良闫大海颜景志颜田杨朝文杨帆杨冯帆杨何文杨佳盈杨莉莉杨明洁杨睿智杨深邦姚玉华姚志国叶一锰尹丽巧尹娜游晓浩游智勇于艳红袁强岳华曾厚敦曾婷轩曾玮查敏张彬彬张丰张海明张恒英张建立张丽霞张力张鹏飞张佩佩张瑞张少博张少如张寿山张潇张笑鹏张云峰张毅张勇赵兵赵静赵雷赵立志赵世平郑福周斌周浩周佳能周猛周平周荣周勋秀祝成光祝凤荣朱辉朱科军左雄 LHAASO Collaboration Key Laboratory of Particle Astrophyics&Experimental Physics Division&Computing Center Institute of High Energy PhysicsChinese Academy of SciencesBeijing 100049China University of Chinese Academy of Sciences Beijing 100049China Tianfu Cosmic Ray Research Center Chengdu 610000China Dublin Institute for Advanced Studies 31 Fitzwilliam Place2 DublinIreland Max-Planck-Institut for Nuclear Physics P.O.Box 10398069029 HeidelbergGermany State Key Laboratory of Particle Detection and Electronics China University of Science and Technology of China Hefei 230026China School of Physical Science and Technology&School of Information Science and Technology Southwest Jiaotong UniversityChengdu 610031China School of Astronomy and Space Science Nanjing UniversityNanjing 210023China Center for Astrophysics Guangzhou UniversityGuangzhou 510006China Hebei Normal University Shijiazhuang 050024China Key Laboratory of Dark Matter and Space Astronomy&Key Laboratory of Radio Astronomy Purple Mountain ObservatoryChinese Academy of SciencesNanjing 210023China Tsung-Dao Lee Institute&School of Physics and Astronomy Shanghai Jiao Tong UniversityShanghai 200240China Key Laboratory for Research in Galaxies and Cosmology Shanghai Astronomical ObservatoryChinese Academy of SciencesShanghai 200030China Key Laboratory of Cosmic Rays(Tibet University) Ministry of EducationLhasa 850000TibetChina National Astronomical Observatories Chinese Academy of SciencesBeijing 100101China School of Physics and Astronomy(Zhuhai)&School of Physics(Guangzhou)&Sino-French Institute of Nuclear Engineering and Technology(Zhuhai) Sun Yat-sen UniversityZhuhai 519000&Guangzhou 510275China School of Physics and Astronomy Yunnan UniversityKunming 650091China Département de Physique Nucléaire et Corpusculaire Facultéde SciencesUniversitéde Genève24 Quai Ernest Ansermet1211 GenevaSwitzerland Institute of Frontier and Interdisciplinary Science Shandong UniversityQingdao 266237China APC Universit'e Paris Cit'eCNRS/IN2P3CEA/IRFUObservat

The full array of the Large High Altitude Air Shower Observatory(LHAASO)has been in operation since July *** its kilometer-square array(KM2A),we optimized the selection criteria for very high and ultrahigh energyγ-rays using data collected from August 2021 to August 2022,resulting in an improvement in significance of the detection in the Crab Nebula of approximately 15%,compared with that of previous *** the implementation of these new selection criteria,the angular resolution was also significantly improved by approximately 10%at tens of *** aspects of the full KM2A array performance,such as the pointing error,were also calibrated using the Crab *** resulting energy spectrum of the Crab Nebula in the energy range of 10-1000 TeV are well fitted by a log-parabola model,which is consistent with the previous results from LHAASO and other experiments.

关键词： γ-ray Crab Nebula significance

Electrically tunable Floquet Weyl photon emission from Dirac semimetal

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arXiv 2025年

作者： Mishra, Sobhan Subhra Tan, Thomas CaiWei Gupta, Manoj Xiu, Faxian Singh, Ranjan Division of Physics and Applied Physics School of Physical and Mathematical Sciences Nanyang Technological University Singapore637371 Singapore Centre for Disruptive Photonic Technologies Nanyang Technological University Singapore639798 Singapore State Key Laboratory of Surface Physics Department of Physics Fudan University Shanghai200433 China Institute for Nanoelectronic Devices and Quantum Computing Fudan University Shanghai200433 China Shanghai Research Center for Quantum Sciences Shanghai201315 China Department of Electrical Engineering University of Notre Dame Notre DameIN United States

The ability to optically engineer the Dirac band and electrically control the Fermi level in two-dimensional (2D) Dirac systems, such as graphene, has significantly advanced quantum technologies. However, similar tunability has remained elusive in three-dimensional (3D) Dirac systems. In this work, we demonstrate both optical and electrical tunability of the band structure in the 3D Dirac semimetal Cd3As2 . Photoexcitation with circularly polarized light breaks time-reversal symmetry, lifting the degeneracy at Dirac points to transform the material into a Floquet Weyl semimetal with chiral Weyl nodes. This transition induces nonzero Berry curvature, giving rise to helicity-dependent transverse anomalous photocurrents, detectable through terahertz (THz) emission at normal incidence. Furthermore, applying an external electric field displaces the Fermi level away from the Dirac point, enlarging the Dirac cone projection leading to a reduced density of states (DoS) of Fermi arcs. As a result, we achieve precise electrical control over Floquet band engineering, resulting in a large modulation of THz emission. Moreover, at oblique incidence, the circular photon-drag effect induces helicity-dependent longitudinal photocurrents. Simultaneous generation and manipulation of both longitudinal and transverse photocurrents enable precise control of the helicity of emitted THz pulses. These results pave the way for electric field-controlled Floquet Weyl THz sources, offering significant potential for applications in quantum computing and low-power electronics. © 2025, CC BY.

关键词： Fermi level

A Novel Human-Based Meta-Heuristic Algorithm: Dragon Boat Optimization

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arXiv 2023年

作者： Li, Xiang Lan, Long Lahza, Husam Yang, Shaowu Wang, Shuihua Yang, Wenjing Liu, Hengzhu Zhang, Yudong College of Computer Science and Technology National University of Defense Technology Changsha410073 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Biological Sciences Xi’an Jiaotong-Liverpool University Jiangsu Suzhou215123 China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom School of Computer Science and Engineering Southeast University Jiangsu Nanjing210096 China Department of Mathematical Sciences University of Liverpool LiverpoolL69 3BX United Kingdom

(Aim) Dragon Boat Racing, a popular aquatic folklore team sport, is traditionally held during the Dragon Boat Festival. Inspired by this event, we propose a novel human-based meta-heuristic algorithm called dragon boat optimization (DBO) in this paper. (Method) It models the unique behaviors of each crew member on the dragon boat during the race by introducing social psychology mechanisms (social loafing, social incentive). Throughout this process, the focus is on the interaction and collaboration among the crew members, as well as their decision-making in different situations. During each iteration, DBO implements different state updating strategies. By modelling the crew's behavior and adjusting the state updating strategies, DBO is able to maintain high-performance efficiency. (Results) We have tested the DBO algorithm with 29 mathematical optimization problems and 2 structural design problems. (Conclusion) The experimental results demonstrate that DBO is competitive with state-of-the-art meta-heuristic algorithms as well as conventional methods. © 2023, CC BY.

关键词： Structural optimization

DULDA: Dual-domain Unsupervised Learned Descent Algorithm for PET image reconstruction

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arXiv 2023年

作者： Hu, Rui Chen, Yunmen Kim, Kyungsang Rockenbach, Marcio Aloisio Bezerra Cavalcanti Li, Quanzheng Liu, Huafeng State Key Laboratory of Modern Optical Instrumentation Department of Optical Engineering Zhejiang University Hangzhou310027 China Department of Mathematics University of Florida GainesvilleFL32611 United States The Center for Advanced Medical Computing and Analysis Massachusetts General Hospital Harvard Medical School BostonMA02114 United States Center for Clinical Data Science Massachusetts General Brigham BostonMA02116 United States

Deep learning based PET image reconstruction methods have achieved promising results recently. However, most of these methods follow a supervised learning paradigm, which rely heavily on the availability of high-quality training labels. In particular, the long scanning time required and high radiation exposure associated with PET scans make obtaining these labels impractical. In this paper, we propose a dual-domain unsupervised PET image reconstruction method based on learned descent algorithm, which reconstructs high-quality PET images from sinograms without the need for image labels. Specifically, we unroll the proximal gradient method with a learnable l2,1 norm for PET image reconstruction problem. The training is unsupervised, using measurement domain loss based on deep image prior as well as image domain loss based on rotation equivariance property. The experimental results demonstrate the superior performance of proposed method compared with maximum-likelihood expectation–maximization (MLEM), total-variation regularized EM (EM-TV) and deep image prior based method (DIP). Copyright © 2023, The Authors. All rights reserved.

关键词： Image reconstruction

Fair Efficiency Comparisons of Decoy-state Quantum key Distribution Protocols

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Chinese Journal of Electronics 2018年第2期27卷 241-249页

作者： LI Hongxin GAO Ming YAN Xueping YAN Bao HAN Yu SHAN Ling MA Zhi Information Engineering University State Key Laboratory of Mathematical Engineering and Advanced Computing College of Animal Science and Technology Henan University of Science and Technology

Taking the schemes based on different formulas of secure key rate as examples, we give a fair comparison between typical protocols under Universal composable(UC) security frame. Through analyzing the relationship of security parameters in post-processing stage and final secure key rate, we achieve the unified quantification between protocols based on Gottesman-Lo-L¨utkenhausPreskill(GLLP) formula and the ones under UC *** on the above research, the impact of different sending lengths and secure parameters on secure key rate is investigated. Besides, we analyze the conditions of fair comparison, and for the first time we give a fair comparison between the protocols based on GLLP formula and smooth entropy. By typical efficiency comparisons, we summarize the way for improving secure key rate in the light intensity choice and the single bit error rate estimation method.

关键词： Quantum key distribution(QKD) Finite-key Universal composable(UC) Fair comparison

EAFP-Med: An Efficient Adaptive Feature Processing Module Based on Prompts for Medical Image Detection

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arXiv 2023年

作者： Li, Xiang Lan, Long Lahza, Husam Yang, Shaowu Wang, Shuihua Yang, Wenjing Liu, Hengzhu Zhang, Yudong College of Computer Science and Technology National University of Defense Technology Changsha410073 China Institute for Quantum Information State Key Laboratory of High Performance Computing College of Computer Science and Technology National University of Defense Technology Changsha410073 China Department of Information Technology Faculty of Computing and Information Technology King Abdulaziz University Jeddah21589 Saudi Arabia Department of Biological Sciences Xi'an Jiaotong-Liverpool University Jiangsu Suzhou215123 China School of Computing and Mathematical Sciences University of Leicester LeicesterLE1 7RH United Kingdom School of Computer Science and Engineering Southeast University Jiangsu Nanjing210096 China Department of Mathematical Sciences University of Liverpool LiverpoolL69 3BX United Kingdom

In the face of rapid advances in medical imaging, cross-domain adaptive medical image detection is challenging due to the differences in lesion representations across various medical imaging technologies. To address this issue, we draw inspiration from large language models to propose EAFP-Med, an efficient adaptive feature processing module based on prompts for medical image detection. EAFP-Med can efficiently extract lesion features of different scales from a diverse range of medical images based on prompts while being flexible and not limited by specific imaging techniques. Furthermore, it serves as a feature preprocessing module that can be connected to any model front-end to enhance the lesion features in input images. Moreover, we propose a novel adaptive disease detection model named EAFP-Med ST, which utilizes the Swin Transformer V2 – Tiny (SwinV2-T) as its backbone and connects it to EAFP-Med. We have compared our method to nine state-of-the-art methods. Experimental results demonstrate that EAFP-Med ST achieves the best performance on all three datasets (chest X-ray images, cranial magnetic resonance imaging images, and skin images). EAFP-Med can efficiently extract lesion features from various medical images based on prompts, enhancing the model's performance. This holds significant potential for improving medical image analysis and diagnosis. © 2023, CC BY.

关键词： Magnetic resonance imaging