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Deep learning–based MRI translation can shorten scans, yet existing models often struggle with whole-body settings because anatomical regions show highly heterogeneous feature distributions and lesions introduce additional cross-modality variability. This work proposes Heterogeneity-Adaptive Diffusion Schrödinger Bridge (HA-DSB), which models translation as stochastic transport between source and target distributions, using region context embeddings from a vision-language model and PET-guided dual-stage guidance for lesion-aware reconstruction.",{"@graph":69,"@context":122},[70,84,105],{"@type":71,"itemListElement":72},"BreadcrumbList",[73,77,79,82],{"item":74,"name":75,"@type":76,"position":8},"https://docshare.wps.com","Home","ListItem",{"item":78,"name":9,"@type":76,"position":14},"https://docshare.wps.com/document/",{"item":80,"name":40,"@type":76,"position":81},"https://docshare.wps.com/document/research-report/",3,{"item":83,"name":65,"@type":76,"position":19},"https://docshare.wps.com/document/heterogeneity-adaptive-diffusion-schrodinger-bridge-for-pet-guided-whole-body-mri-translation/328202/",{"url":83,"name":65,"@type":85,"image":86,"author":91,"headline":65,"publisher":94,"fileFormat":97,"inLanguage":63,"description":67,"dateModified":98,"datePublished":99,"encodingFormat":97,"isAccessibleForFree":100,"interactionStatistic":101},"DigitalDocument",{"url":87,"@type":88,"width":89,"height":90},"https://docshare.wps.com/thumbnails/heterogeneity-adaptive-diffusion-schrodinger-bridge-for-pet-guided-whole-body-mri-translation/328202.png","ImageObject",300,407,{"name":92,"@type":93},"Seraphina","Person",{"url":74,"name":95,"@type":96},"DocShare","Organization","application/pdf","2026-10-23","2026-09-21",true,{"@type":102,"interactionType":103,"userInteractionCount":44},"InteractionCounter",{"@type":104},"ViewAction",{"@type":106,"mainEntity":107},"FAQPage",[108,114,118],{"name":109,"@type":110,"acceptedAnswer":111},"Why is whole-body PET–MR scan time a major obstacle in clinical practice?","Question",{"text":112,"@type":113},"Whole-body PET–MR typically requires 60–90 minutes due to multiple MR sequences, which reduces clinical efficiency and increases patient discomfort.","Answer",{"name":115,"@type":110,"acceptedAnswer":116},"What makes whole-body MRI translation more difficult than region-specific translation?",{"text":117,"@type":113},"Whole-body scans exhibit strong cross-region heterogeneity, with non-stationary, region-dependent intensity distributions that increase the difficulty of learning a unified mapping.",{"name":119,"@type":110,"acceptedAnswer":120},"How does HA-DSB incorporate PET guidance to improve lesion fidelity?",{"text":121,"@type":113},"HA-DSB integrates lesion-aware metabolic priors into bridge dynamics via dual-stage guidance: PET-guided noise modulation in the forward process and PET-feature-driven attention in the reverse process to amplify lesion-relevant structures.","https://schema.org",{"og:url":83,"og:type":124,"og:title":65,"og:site_name":95,"og:description":67},"article",{"robots":126,"canonical":83},"index,follow",{"doc_id":128,"site_id":62},328202,1790193636,{"code":4,"msg":5,"data":131},{"doc_id":128,"user_id":132,"nickname":92,"user_avatar":133,"doc_module":4,"category_id":39,"category_name":40,"doc_title":65,"doc_description":67,"doc_content":134,"file_id":135,"file_url":136,"file_type":137,"file_size":138,"view_count":44,"is_deleted":4,"is_public":8,"is_downloadable":8,"audit_status":8,"page_count":52,"language":139,"language_code":63,"site_id":62,"html_lang":63,"table_of_contents":140,"faqs":141,"seo_title":142,"seo_description":67,"update_tm":143,"read_time":144,"preview_page_count":4},962075114101,"https://ap-avatar.wpscdn.com/avatar/e000253a75eb197efd?x-image-process=image/resize,m_fixed,w_180,h_180&k=1780044092746381165","arXiv :2607 .0740 1v 1 [ cs .CV] 8 Jul 2026  \nHeterogeneity-Adaptive Diffusion Schrödinger Bridge for PET-Guided Whole-Body MRI  \nTranslation  \nChengbo Wang 1†, Jiacheng Yu 1†, Linjie Bian2†, Ming Qi2 , Xiaosheng Liu2 , Tongtong Che3 , Jichang Zhang3 , Shuyu Li3 , and Shaoli Song2 * and Xiuying  \nWang 1 *  \n1 The University of Sydney, Sydney, Australia  \n2 Department of Nuclear Medicine, Fudan University Shanghai Cancer Center, Shanghai, China  \n3 State Key Laboratory of Cognitive Neuroscience and Learning, Beijing Normal University, Beijing, China  \n.  \nAbstract. While whole-body multimodal medical imaging scanners have been increasingly recognized for more effective medical applications, the excessive long acquisition time in PET–MR scanning is a major obstacle in more efficient clinical practice. Deep learning–based MRI translation provides a potential solution to reduce scan duration. However, current models often focus on specific anatomical regions and face challenges for whole-body scans that consists of highly heterogeneous feature distributions mainly due to (1) different anatomical regions across whole-body, and (2) lesions or pathological tissues. This paper tackles the challenges through a novel Heterogeneity-Adaptive Diffusion Schrödinger Bridge (HA-DSB) framework. By explicitly modeling translation as stochastic transport between source and target distributions, HA-DSB incorporates region context embeddings derived from a vision-language model (VLM) to enable region-specific modeling. To enhance fidelity of the pathological tissue, lesion-aware metabolic prior from PET is integrated directly into the bridge dynamics through a dual-stage guidance mechanism. Specifically, a PET-guided noise modulation module adaptively scales spatial diffusion perturbations during the forward process, while PET features are leveraged during the reverse process to selectively amplify lesion-relevant structures via an attention mechanism. Experiments demonstrate the superiority of our method across different body regions in whole-body MRI translation and show improved translation quality in lesion areas under PET guidance. Our code is available at [https://github.com/xyw-medical-research/HADSB](https://github.com/xyw-medical-research/HADSB).  \nKeywords: Medical Image Translation · PET/MR Imaging · Diffusion Schrödinger Bridge · Whole-body MR Translation  \n† contributed equally to this [work.](work. cw643@cantab.ac.uk)[ cw643@cantab.ac.uk](work. cw643@cantab.ac.uk), [mryu888@foxmail.com](mryu888@foxmail.com), [blijer@163.com](blijer@163.com)  \n* corresponding authors.  \n2 C. Wang et al.  \n1 Introduction  \nHybrid positron emission tomography combined with magnetic resonance imaging (PET/MR) is an emerging imaging modality that enables simultaneous acquisition of metabolic and high-resolution anatomical information, producing intrinsically co-registered PET and multi-sequence MR images while reducing radiation exposure compared with PET/CT [1] . Whole-body PET/MR supports comprehensive multi-bed imaging from the head and neck to the mid-thigh and has become increasingly important in clinical applications such as cancer metastasis evaluation [2] . However, whole-body PET/MR scan time typically ranges from 60–90 minutes, largely due to multiple MR sequences, which limits clinical efficiency and increases patient discomfort. Deep learning–based MR translation offers a practical solution by synthesizing time-consuming modalities from fastacquired sequences, and recent diffusion-based approaches have demonstrated promising performance in MR image translation [3–6] .  \nHowever, most MR translation focus on specific anatomical regions such asthe brain in public datasets [7], and extending these models to whole-body MR translation in integrated PET/MR settings remains challenging. Wholebody scans exhibit strong cross-region heterogeneity, with substantial variations in tissue composition and signal characteristics across anatomical regions [8] ","cbCaihbi6fXSFU6j","https://ap.wps.com/l/cbCaihbi6fXSFU6j","pdf",27418629,"English","# Abstract\n# Introduction\n## Challenges in whole-body PET/MR translation\n## Proposed Heterogeneity-Adaptive Diffusion Schrödinger Bridge (HA-DSB)","[{\"question\":\"Why is whole-body PET–MR scan time a major obstacle in clinical practice?\",\"answer\":\"Whole-body PET–MR typically requires 60–90 minutes due to multiple MR sequences, which reduces clinical efficiency and increases patient discomfort.\"},{\"question\":\"What makes whole-body MRI translation more difficult than region-specific translation?\",\"answer\":\"Whole-body scans exhibit strong cross-region heterogeneity, with non-stationary, region-dependent intensity distributions that increase the difficulty of learning a unified mapping.\"},{\"question\":\"How does HA-DSB incorporate PET guidance to improve lesion fidelity?\",\"answer\":\"HA-DSB integrates lesion-aware metabolic priors into bridge dynamics via dual-stage guidance: PET-guided noise modulation in the forward process and PET-feature-driven attention in the reverse process to amplify lesion-relevant structures.\"}]","Heterogeneity-Adaptive Diffusion Schrödinger Bridge for PET-Guided Whole-Body MRI Translation | PDF",1789978826,25]