[{"data":1,"prerenderedAt":-1},["ShallowReactive",2],{"doc-detail-120529-en":3,"doc-seo-120529-105":30,"detail-sidebar-cat-0-en-105":91},{"code":4,"msg":5,"data":6},0,"success",{"doc_id":7,"user_id":8,"nickname":9,"user_avatar":10,"doc_module":4,"category_id":11,"category_name":12,"doc_title":13,"doc_description":14,"doc_content":15,"file_id":16,"file_url":17,"file_type":18,"file_size":19,"view_count":4,"is_deleted":4,"is_public":20,"is_downloadable":20,"audit_status":20,"page_count":21,"language":22,"language_code":23,"site_id":24,"html_lang":23,"table_of_contents":25,"faqs":26,"seo_title":27,"seo_description":14,"update_tm":28,"read_time":29},120529,1374391974585,"Genevieve","https://ap-avatar.wpscdn.com/davatar_276721f389ce27ea32af1340a28f341c",8,"Research & Report","Three-Dimensional, Multimodal Synchrotron Data for Machine Learning Applications - Research","Machine learning techniques increasingly support medical and physical sciences, yet high-quality training data remains a central constraint. This work introduces a spatially resolved, three-dimensional, multimodal, multi-resolution synchrotron dataset for a bespoke zinc-doped Zeolite 13X sample. Multi-resolution micro X-ray computed tomography characterizes pore structure, while spatially resolved X-ray diffraction computed tomography maps homogeneous sodium and zinc phases. Both raw and processed data are released via Zenodo to enable deep learning, super-resolution, multimodal fusion, and 3D reconstruction development.","arXiv :2409 .07322v1 [ cs .LG] 11 Sep 2024  \nThree-Dimensional, Multimodal Synchrotron Data for Machine Learning Applications  \nCalum Green 1,2,* , Sharif Ahmed2 , Shashidhara Marathe2 , Liam Perera2 , Alberto Leonardi2 , Killian Gmyrek 1 , Daniele Dini 1 , and James Le Houx3,4  \n1 Imperial College London, Department of Mechanical Engineering, London, SW7 2AZ, United Kingdom  \n2 Diamond Light Source, Rutherford Appleton Laboratory, Didcot, OX11 0QX, United Kingdom  \n3 ISIS Neutron & Muon Source, Rutherford Appleton Laboratory, Didcot, OX11 0QX, United Kingdom  \n4The Faraday Institution, Harwell Science and Innovation Campus, Didcot, OX11 0RA, United Kingdom  \n* corresponding author: Calum Green ([cg1417@ic.ac.uk](cg1417@ic.ac.uk))  \nABSTRACT  \nMachine learning techniques are being increasingly applied in medical and physical sciences across a variety of imaging modalities; however, an important issue when developing these tools is the availability of good quality training data. Here we present a unique, multimodal synchrotron dataset of a bespoke zinc-doped Zeolite 13X sample that can be used to develop advanced deep learning and data fusion pipelines. Multi-resolution micro X-ray computed tomography was performed on a zinc-doped Zeolite 13X fragment to characterise its pores and features, before spatially resolved X-ray diffraction computed tomography was carried out to characterise the homogeneous distribution of sodium and zinc phases. Zinc absorption was controlled to create a simple, spatially isolated, two-phase material. Both raw and processed data is available as a series of Zenodo entries. Altogether we present a spatially resolved, three-dimensional, multimodal, multi-resolution dataset that can be used for the development of machine learning techniques. Such techniques include development of super-resolution, multimodal data fusion, and 3D reconstruction algorithm development.  \nBackground & Summary  \nMachine learning and the use of deep learning architectures such as convolutional neural networks (CNNs), generative adversarial networks (GANs) and diffusion models have successfully been adopted in the medical imaging community fortasks such as segmentation, classification, super-resolution, and data fusion.1–4 Data fusion, the combination of two or more datasets (modalities), is a powerful tool that can create a new fused dataset that contains the best features of each datasetsuch as resolution and field-of-view, or contains complementary information such as chemical and spatial information.5 Deep learning techniques are implemented on 3D X-ray imaging within the physical sciences, such as the digital rocks community using GANs for super-resolution sandstone images; Li-ion battery research using 3D U-Nets for electrode segmentation of 3D volumes; and even fusion of complementary 2D and 3D imaging datasets of different spatial resolutions.6–8 However, a key issue when working with deep learning architectures is the availability of good quality training data. For super-resolution tasks, this presents itself in the form of having spatially aligned high and low-resolution images. Whereas for data fusion tasks availability of two spatially resolved modalities of the same sample is extremely important, but rarely exists or is difficult to obtain.  \nSynchrotron facilities provide extremely large photon flux, and can provide higher spatial and temporal resolutions than traditional lab-based X-ray equipment and experiments. They also feature the capability of having an experimental setup that can allow simultaneous acquisition of different modalities in-situ. Such setups include the capability to obtain imaging and diffraction data to characterise spatial information and understand the phase description as is performed on the K11 beamline at Diamond Light Source.  \nIn this work present a multi-resolution X-ray Computed Tomography (XCT) dataset acquired on the I13-2 micro-imaging beamline, and a spatially resolved X-ray Diffr","cbCairKMAYEMmcs9","https://ap.wps.com/l/cbCairKMAYEMmcs9","pdf",8048600,1,9,"English","en",105,"# Abstract\n# Background & Summary\n# Zinc-Doped Zeolite 13X\n# Datasets and Reuse Potential","[{\"question\":\"What does the dataset enable for machine learning model development?\",\"answer\":\"The dataset supports advanced deep learning and data fusion workflows, including super-resolution, multimodal data fusion, and 3D reconstruction algorithm development.\"},{\"question\":\"How are pore and phase information obtained in the presented measurements?\",\"answer\":\"Multi-resolution micro X-ray computed tomography characterizes the pores and features, while spatially resolved X-ray diffraction computed tomography describes the homogeneous distribution of sodium and zinc phases.\"},{\"question\":\"Why was zinc doping used for the Zeolite 13X sample?\",\"answer\":\"Zinc absorption was controlled to create a simple, spatially isolated two-phase material, and zinc also introduces a k-edge that enables future modalities such as X-ray fluorescence spectroscopy.\"}]","Three-Dimensional, Multimodal Synchrotron Data for Machine Learning Applications - Research | PDF",1785730513,23,{"code":4,"msg":31,"data":32},"ok",{"site_id":24,"language":23,"slug":33,"title":13,"keywords":34,"description":14,"schema_data":35,"social_meta":86,"head_meta":88,"extra_data":90,"updated_unix":28},"three-dimensional-multimodal-synchrotron-data-for-machine-learning-applications-research","",{"@graph":36,"@context":85},[37,54,68],{"@type":38,"itemListElement":39},"BreadcrumbList",[40,44,48,51],{"item":41,"name":42,"@type":43,"position":20},"https://docshare.wps.com","Home","ListItem",{"item":45,"name":46,"@type":43,"position":47},"https://docshare.wps.com/document/","Document",2,{"item":49,"name":12,"@type":43,"position":50},"https://docshare.wps.com/document/research-report/",3,{"item":52,"name":13,"@type":43,"position":53},"https://docshare.wps.com/document/three-dimensional-multimodal-synchrotron-data-for-machine-learning-applications-research/120529/",4,{"url":52,"name":13,"@type":55,"author":56,"headline":13,"publisher":58,"fileFormat":61,"inLanguage":23,"description":14,"dateModified":62,"datePublished":62,"encodingFormat":61,"isAccessibleForFree":63,"interactionStatistic":64},"DigitalDocument",{"name":9,"@type":57},"Person",{"url":41,"name":59,"@type":60},"DocShare","Organization","application/pdf","2026-08-03",true,{"@type":65,"interactionType":66,"userInteractionCount":4},"InteractionCounter",{"@type":67},"ViewAction",{"@type":69,"mainEntity":70},"FAQPage",[71,77,81],{"name":72,"@type":73,"acceptedAnswer":74},"What does the dataset enable for machine learning model development?","Question",{"text":75,"@type":76},"The dataset supports advanced deep learning and data fusion workflows, including super-resolution, multimodal data fusion, and 3D reconstruction algorithm development.","Answer",{"name":78,"@type":73,"acceptedAnswer":79},"How are pore and phase information obtained in the presented measurements?",{"text":80,"@type":76},"Multi-resolution micro X-ray computed tomography characterizes the pores and features, while spatially resolved X-ray diffraction computed tomography describes the homogeneous distribution of sodium and zinc phases.",{"name":82,"@type":73,"acceptedAnswer":83},"Why was zinc doping used for the Zeolite 13X sample?",{"text":84,"@type":76},"Zinc absorption was controlled to create a simple, spatially isolated two-phase material, and zinc also introduces a k-edge that enables future modalities such as X-ray fluorescence spectroscopy.","https://schema.org",{"og:url":52,"og:type":87,"og:title":13,"og:site_name":59,"og:description":14},"article",{"robots":89,"canonical":52},"index,follow",{"doc_id":7,"site_id":24},{"code":4,"msg":5,"data":92},[93,97,101,105,110,115,120,123,127,130,134],{"id":20,"doc_module":4,"doc_module_name":46,"category_name":94,"show_sort_weight":95,"slug":96},"Story & Novel",90,"story-novel",{"id":47,"doc_module":4,"doc_module_name":46,"category_name":98,"show_sort_weight":99,"slug":100},"Literature",80,"literature",{"id":53,"doc_module":4,"doc_module_name":46,"category_name":102,"show_sort_weight":103,"slug":104},"Exam",70,"exam",{"id":106,"doc_module":4,"doc_module_name":46,"category_name":107,"show_sort_weight":108,"slug":109},5,"Comic",60,"comic",{"id":111,"doc_module":4,"doc_module_name":46,"category_name":112,"show_sort_weight":113,"slug":114},6,"Technology",50,"technology",{"id":116,"doc_module":4,"doc_module_name":46,"category_name":117,"show_sort_weight":118,"slug":119},7,"Healthcare",40,"healthcare",{"id":11,"doc_module":4,"doc_module_name":46,"category_name":12,"show_sort_weight":121,"slug":122},30,"research-report",{"id":21,"doc_module":4,"doc_module_name":46,"category_name":124,"show_sort_weight":125,"slug":126},"Religion & Spirituality",20,"religion-spirituality",{"id":125,"doc_module":4,"doc_module_name":46,"category_name":128,"show_sort_weight":125,"slug":129},"World Cup","world-cup",{"id":131,"doc_module":4,"doc_module_name":46,"category_name":132,"show_sort_weight":131,"slug":133},10,"Lifestyle","lifestyle",{"id":135,"doc_module":4,"doc_module_name":46,"category_name":136,"show_sort_weight":106,"slug":137},19,"General","general"]