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University of Michigan(密歇根大学安娜堡分校)

2026-05-15 至 2026-05-15 共收录 4
2507.01909 2026-05-15 cs.CV

Modality-agnostic, patient-specific digital twins modeling temporally varying digestive motion

模态无关、患者特异性的数字双胞胎建模时变消化运动

Jorge Tapias Gomez, Nishant Nadkarni, Lando S. Bosma, Jue Jiang, Ergys D. Subashi, William P. Segars, James M. Balter, Mert R Sabuncu, Neelam Tyagi, Harini Veeraraghavan

机构 * Computer and Information Science, Cornell University(康奈尔大学计算机与信息科学系) Department of Medical Physics, Memorial Sloan Kettering Cancer Center(纪念斯隆凯特琳癌症中心医学物理系) University Medical Center Utrecht(乌得勒支大学医学中心) Department of Radiation Physics, University of Texas MD Anderson Cancer Center(德克萨斯大学MD安德森癌症中心放射物理系) Carl E. Ravin Advanced Imaging Laboratories and Center for Virtual Imaging Trials, Duke University Medical Center(杜克大学医学中心卡尔·E·拉文高级影像实验室和虚拟影像试验中心) Department of Radiation Oncology, University of Michigan(密歇根大学放射肿瘤学系)

AI总结 本文提出一种模态无关的患者特异性数字双胞胎建模方法,用于评估变形图像配准方法的准确性,通过生成21个运动阶段的4D序列,评估DIR方法的性能。

Comments This work is still review, it contains 7 Pages, 6 figures, and 4 tables

Journal ref Phys. Med. Biol. 71 (2026) 015029

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2605.14301 2026-05-15 cs.LG stat.ML

Language-Induced Priors for Domain Adaptation

领域适应中的语言诱导先验

Qiyuan Chen, Jiayu Zhou, Raed Al Kontar

机构 * University of Michigan(密歇根大学)

AI总结 本文提出语言诱导先验(LIP)用于领域适应,通过利用目标领域的专家描述,结合预训练大语言模型学习偏好,改进源域选择并提升性能。

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2511.05159 2026-05-15 stat.ML cs.LG

A New Framework for Convex Clustering in Kernel Spaces: Finite Sample Bounds, Consistency and Performance Insights

核空间中凸聚类的新框架:有限样本界、一致性和性能洞察

Shubhayan Pan, Kushal Bose, Debolina Paul, Saptarshi Chakraborty, Swagatam Das

机构 * Indian Statistical Institute, Kolkata(印度统计研究院,加尔各答) Electronics and Communication Sciences Unit, Indian Statistical Institute(印度统计研究院电子与通信科学单位) Department of Statistics, University of Oxford(牛津大学统计系) Department of Statistics, University of Michigan(密歇根大学统计系)

AI总结 本文提出核化凸聚类方法,通过映射数据到RKHS空间,解决线性不可分和非凸数据的聚类问题,理论分析和实验验证显示其优于现有方法。

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2508.14950 2026-05-15 eess.IV cs.LG

Potential and challenges of generative adversarial networks for super-resolution in 4D Flow MRI

生成对抗网络在4D流体磁共振成像超分辨率中的潜力与挑战

Oliver Welin Odeback, Arivazhagan Geetha Balasubramanian, Jonas Schollenberger, Edward Ferdiand, Alistair A. Young, C. Alberto Figueroa, Susanne Schnell, Outi Tammisola, Ricardo Vinuesa, Tobias Granberg, Alexander Fyrdahl, David Marlevi

机构 * Surgery, Karolinska Institutet , addressline= Karolinska Universitetssjukhuset Solna (L1:00) , city= Stockholm , postcode= 171 76 , country= Sweden organization= FLOW, Engineering Mechanics, KTH Royal Institute of Technology , addressline= Osquars Backe 18 , city= Stockholm , postcode= 100 44 , country= Sweden organization= Department of Radiology Biomedical Imaging, University of California San Francisco , addressline= 505 Parnassus Avenue , city= San Francisco , postcode= 94143 , state= CA , country= USA organization= Faculty of Informatics, Telkom University , addressline= Jl.Telekomunikasi No. 1, Terusan Buahbatu , city= Bandung , postcode= 40257 , state= West Java , country= Indonesia organization= Auckland Bioengineering Institute, University of Auckland , addressline= Bioengineering House, 70 Symonds St , city= Grafton , postcode= 1010 , country= New Zealand organization= School of Biomedical Engineering \& Imaging Sciences, King's College London , addressline= 1 Lambeth Palace Rd, South Bank , city= London , postcode= SE1 7EU , country= UK organization= Department of Biomedical Engineering, University of Michigan , addressline= 1107 Carl A. Gerstacker Bldg 2200 Bonisteel Blvd. , city= Ann Arbor , postcode= 48109-2099 , state= MI , country= USA organization= Department of Physics, University of Greifswald , addressline= Felix-Hausdorff-Str. 6 , city= Greifswald , postcode= 174 89 , country= Germany organization= Department of Aerospace Engineering, University of Michigan , addressline= 1320 Beal Avenue , city= Ann Arbor , postcode= 48109-2140 , state= MI , country= USA organization= Department of Neuroradiology, Karolinska University Hospital , addressline= Hälsovägen 13, O42 , city= Stockholm , postcode= 141 86 , country= Sweden organization= Department of Clinical Physiology, Karolinska University Hospital , addressline= Eugeniavägen 3, A8:01 , city= Solna , postcode= 171 64 , country= Sweden organization= Institute for Medical Engineering Science, Massachusetts Institute of Technology , addressline= 45 Carleton St , city= Cambridge , postcode= 02142 , state= MA , country= USA

AI总结 本文研究了生成对抗网络在4D流体磁共振成像超分辨率中的应用,通过对比不同对抗损失函数,发现Wasserstein GAN在稳定性和性能上表现最佳,提升了近壁速度恢复效果。

Comments 26 pages, 10 figures

Journal ref Computers in Biology and Medicine 211 (2026) 111745

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