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Stansby, D.

Publications and source records attributed to Stansby, D..

3 recordsLinked to original sources

The Extremely Brilliant Brain: An Isotropic Microscale Human Brain Dataset

We present an isotropic 7.72 {micro}m/voxel post-mortem human brain dataset acquired using Hierarchical Phase-Contrast Tomography (HiP-CT) at the ESRF Extremely Brilliant Source, beamline BM18. This fills a critical gap between whole-brain MRI at 100 {micro}m resolution and serial-section histological reconstructions at 20 {micro}m or finer. HiP-CT contrast, derived from X-ray phase shifts, enables rich 3D visualisation of complex neuroanatomy including white-matter bundles, microvasculature, and sub-nuclei. We provide open-source workflows for online data exploration, subvolume download, segmentation, and reintegration of analyses into the full dataset. We demonstrate the potential of this resource by tracing vasculature over long distances, segmenting nuclei, and extracting whitematter orientations with 3D structure-tensor analysis. High-resolution human brain datasets are transformative for quantitative neuroanatomy, circuit mapping, and validation of clinical imaging; this openly available resource is a critical step for global access to next-generation multiscale brain imaging.

neuroscience↗

Hierarchical Phase-Contrast Tomography Imaging: Applicability in biomedical research

ObjectivesHierarchical Phase-Contrast Tomography (HiP-CT) enables non-destructive, multi-scale imaging of whole human organs. We describe how HiP-CT is utilized for biomedical research within the Human Organ Atlas Hub through three case studies: mapping the enteric nervous system (ENS) of the human colon, analysing myocardial and AV conduction architecture in Tetralogy of Fallot (TOF), and characterizing ductal organization in breast carcinoma. The challenges we faced with this novel biomedical data are discussed. MethodsWhole-organ and region-of-interest scans of three types of human organs were acquired at the European Synchrotron Radiation Facility (ESRF) with isotropic voxel sizes ranging from 20 {micro}m to 0.8 {micro}m. For the colon, voxel binning and RootPainter were employed to tackle data size to segment the ENS. For the heart, voxel-wise myocyte orientation mapping was calculated in terabyte-scale datasets with a high-performance computational framework (Cardiotensor). Breast carcinoma samples were correlated with histopathology for structure validation. ResultsHiP-CT revealed the large-scale organization of the ENS in the colon, enabling visualisation of the 3D structures of the ENS across the colon In TOF hearts, analysis uncovered abnormal myocardial structure and heterogeneous conduction system morphology. In breast carcinoma, HiP-CT resolved the full hierarchy of ductal structures and vascular relationships within tumour and peritumoral regions. ConclusionsHiP-CT provides unprecedented, hierarchical insight into intact human organ structure, bridging the gap between histology and radiology. Advances in knowledgeHiP-CT establishes a new ex vivo radiological modality capable of linking microscale pathology to whole-organ context, advancing translational research in neurogastroenterology, cardiology, and oncology

biophysics↗

The Human Organ Atlas

We present the Human Organ Atlas (HOA), an open data repository making accessible multiscale 3D imaging of human organs. The repository also provides software tools and training resources enabling worldwide access, sharing, and analysis of these datasets, facilitating further research and the continued expansion of the HOA. The images are generated using a synchrotron imaging technique - Hierarchical Phase-Contrast Tomography (HiP-CT) that uses the ESRFs Extremely Brilliant Source, spanning whole organ imaging at around 20 m/voxel with local volumes of interest within the intact organs imaged down to [~] 1 m/voxel. This offers a comprehensive exploration of human anatomy, providing unparalleled insights into intricate structures and spatial relationships. The Human Organ Atlas offers researchers, clinicians, and educators a valuable resource for anatomical study, image analysis, medical education, and large-scale data mining.

bioinformatics↗