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• Journal article
  Wang J, Ruan D, Li Y, Tan T, Wu L, Yang G, Jiang Met al., 2025,

  Dynamic mask stitching-guided region consistency for semi-supervised 3D medical image segmentation

  , EXPERT SYSTEMS WITH APPLICATIONS, Vol: 292, ISSN: 0957-4174
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• Journal article
  Pan Q, Li Z, Qiao W, Lou J, Yang Q, Yang G, Ji Bet al., 2025,

  AMVLM: Alignment-Multiplicity Aware Vision-Language Model for Semi-Supervised Medical Image Segmentation

  , IEEE TRANSACTIONS ON MEDICAL IMAGING, Vol: 44, Pages: 4307-4322, ISSN: 0278-0062
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• Journal article
  Fang EF, Fang Y, Chen G, Wang H-L, Zhang J, Wu C, Liao J, Xie C, Liu X, Wang K, Liu Y, Yang G, Wang Q, He L-T, Li J, Chen H-Z, Kang L, Jiang Y, Su H, Jiang H, He N, Tao J, Leng SX, Siow RC, Liu C, Khan HTA, Liu Y, Kato H, Sasaki T, Kim JI, Maier AB, Zhang L, Rasmussen LJ, Woo J, Wu J, Zou Het al., 2025,

  Adapting health, economic and social policies to address population aging in China

  , NATURE AGING, Vol: 5, Pages: 2176-2187
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• Journal article
  Jin W, Wang J, Gao Y, Shi B, Wang N, Zhao B, Yang Get al., 2025,

  Self-Adaptive LLM Instructions Optimization for Aspect-Based Sentiment Analysis by Incorporating Emotion-Oriented In-Contexts

  , COMPUTATIONAL INTELLIGENCE, Vol: 41, ISSN: 0824-7935
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• Journal article
  Xie H, Zhao X, Zhang N, Liu J, Yang G, Cao Y, Xu J, Xu L, Sun Z, Wen Z, Chai S, Liu Det al., 2025,

  Machine learning-based hemodynamics quantitative assessment of pulmonary circulation using computed tomographic pulmonary angiography

  , INTERNATIONAL JOURNAL OF CARDIOLOGY, Vol: 437, ISSN: 0167-5273
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• Journal article
  David MCB, Kolanko MA, Parker TD, Nilforooshan R, Zimmerman KA, Bonet Olivares C, Hoang K, Brandt J, Triantafyllou C, Lally PJ, Scott G, Sharp DJ, Malhotra PAet al., 2025,

  Catecholaminergic nucleus integrity and Alzheimer's pathology, symptoms, and progression

  , Alzheimer's and Dementia, Vol: 21, ISSN: 1552-5260

  BACKGROUNDThe noradrenergic locus coeruleus (LC) accumulates pathology early in Alzheimer's disease (AD), with LC dysfunction contributing to symptoms and disease progression. We investigated LC and substantia nigra (SN) integrity in healthy controls and AD participants.METHODSNinety-three AD participants and 29 controls underwent neuromelanin magnetic resonance imaging. LC and SN contrast, reflecting nucleus integrity, related to cognitive and neuropsychiatric symptoms, as well as cognitive decline and atrophy rates.RESULTSLC – but not SN – integrity was reduced in AD versus controls (b = −0.39, p = 0.001) and within AD was associated with global cognition (b = 8.53, p = 0.04) and neuropsychiatric symptoms, accounting for SN. An AD subgroup with reduced SN integrity had worse cognition. LC integrity predicted plasma phosphorylated tau protein 217 (b = −0.30, p = 0.03). Lower LC and SN integrities were both related to faster cognitive decline (LC: b = −4.74, p = 0.048; SN: b = −2.27, p = 0.03), accounting for one another.DISCUSSIONCatecholaminergic nucleus integrity plays an important role in AD. Both systems are relevant to cognitive performance and decline. LC, in particular, relates closely to symptoms, pathology, and rate of progression.HighlightsIn symptomatic AD, LC integrity reflects cortical AD pathology, measured by pTau217.LC integrity predicts cognitive function in AD, independent of cortical atrophy.LC and SN integrity independently relate to attentional performance.Symptoms of anxiety, depression, and apathy are associated with lower LC integrity.LC and SN relate to cognitive decline rate and left LC predicts atrophy rate.

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• Journal article
  Papanastasiou G, Sanchez PP, Christodoulidis A, Yang G, Pinaya WHLet al., 2025,

  Confounder-aware foundation modeling for accurate phenotype profiling in cell imaging

  , npj Imaging, ISSN: 2948-197X

  Image-based profiling is rapidly transforming drug discovery, offering unprecedented insights into cellular responses. However, experimental variability hinders accurate identification of mechanisms of action (MoA) and compound targets. Existing methods commonly fail to generalize to novel compounds, limiting their utility in exploring uncharted chemical space. To address this, we present a confounder-aware foundation model integrating a causal mechanism within a latent diffusion model, enabling the generation of balanced synthetic datasets for robust biological effect estimation. Trained on over 13 million Cell Painting images and 107 thousand compounds, our model learns robust cellular phenotype representations, mitigating confounder impact. We achieve state-of-the-art MoA and target prediction for both seen (0.66 and 0.65 ROC-AUC) and unseen compounds (0.65 and 0.73 ROC-AUC), significantly surpassing real and batch-corrected data. This innovative framework advances drug discovery by delivering robust biological effect estimations for novel compounds, potentially accelerating hit expansion. Our model establishes a scalable and adaptable foundation for cell imaging, holding the potential to become a cornerstone in data-driven drug discovery.

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• Journal article
  Lally P, Jin Y, Huo Z, Beitone C, Chiew M, Matthews P, Miller K, Bangerter Net al., 2025,

  Steady-state free precession for T2* relaxometry: all echoes in every readout with k-space aliasing

  , Magnetic Resonance in Medicine, Vol: 94, Pages: 1563-1576, ISSN: 0740-3194

  PurposeMulti-echo gradient echo imaging is useful for a range of applications including relaxometry, susceptibility mapping, and quantifying relative proportions of fat and water. This relies primarily on long-TR multi-echo gradient echo sequences (FLASH), which by design isolate one signal component (i.e., echo) at a time per readout. In this work, we propose an alternative strategy that simultaneously measures all signal components at once in every readout event with an N-periodic SSFP sequence. Essentially, we Fourier encode the signals into an “F-k space” similar to the “TE-k space” of a multi-echo gradient echo acquisition. This enables an efficient, short-TR relaxometry experiment where signals benefit from averaging effects over multiple excitations.Theory and MethodsIn the presented approach, multiple echoes are recorded simultaneously and separated by their differing phase evolution over multiple TRs. At low flip angles the relative echo amplitudes and phases are equivalent to those acquired sequentially from a multi-echo FLASH, in terms of both T2* weighting and spatial phase distributions. The two approaches were compared for the example of R2* relaxometry in a phantom and in human volunteers.ResultsThe proposed approach shows close agreement in R2* estimation with multi-echo FLASH, with the advantage of more rapid temporal sampling.ConclusionThe proposed approach is a promising alternative to other relaxometry approaches, by measuring signals from multiple echo pathways simultaneously and separating them based on a simple analytical model.

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• Journal article
  Jiang L, Ma L, Yang G, 2025,

  Shadow defense against gradient inversion attack in federated learning☆

  , MEDICAL IMAGE ANALYSIS, Vol: 105, ISSN: 1361-8415
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• Journal article
  Xing Z, Wan L, Fu H, Yang G, Yang Y, Yu L, Lei B, Zhu Let al., 2025,

  Diff-UNet: A diffusion embedded network for robust 3D medical image segmentation

  , MEDICAL IMAGE ANALYSIS, Vol: 105, ISSN: 1361-8415
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  • Citations: 2

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