the accuracy of the segmentation, however, lays a foundation for tools such as machine learning methods for automate d segmentation of blood vasculature from imaging data. hip - ct imaging still cannot resolve afferent arteriole or capillary resolution across the whole organ, meaning that the contributions of peritubular capillaries or vasa recta are not incorporated. this also creates challenges for applying ordering schemes such as the strahler order, where the true 0th order is the capillary bed. previous approaches to estimating the distance of a terminal end in a truncated network from the capillary bed have relied on utilising diameter measurements of vessels to iteratively update the strahler order of terminal ends. this facilitates the creation of a connectivity matrix to estimate the downstream network. however, diameter estimation is less ac curate for hip - ct, where vascular collapse makes radius estimates less consistent than, for example, when using microfill techniques. using the high - resolution vois, we also demonstrated that glomeruli frequently emanate from non - terminal arterioles. without connecting on the order of 1000s of glomeruli back to the main vascular tree as performed for small portions of rat kidney, a connectivity matrix cannot be developed. however, the utility of any vascular classification scheme relies upon the ability to disting uish morphologically distinc t vessel types, and to show logarithmic relations between morphology and classification orders. our truncated strahler approach creates vessel orders which are able to separate morphologically distinc t vessels ( supplementary note 4 ), as well as demonstrating logarithmic relationships for radius and vessel number. we also found that truncated strahler ordering also aligns well with the anatomically defined vessel classifications, as was the case for rat kidney. the future of hip - ct and mapping the kidney vasculature is promising. the upcoming esrf beamline ( bm18 ) enables longer propagation distances than shown here, dramatically increasing the contrast sensitivity for the lower resolution scans. further developments in scanning and data handling have already extended the capabilities of hip - ct to create whole kidney overview datasets, with voxel sizes down to 9 µm / voxel, and to submicron voxel sizes in vois. thus, future studies can leverage the greater detail available on low - resolution scans of the whole kidney, providing the potential to further assess phenomena such as the emergence of glomeruli from non - terminal arterioles, or potentially map entire organs down to the capillary level. as these developments unfold, we have created an open - access data portal ( https: / / human - organ - atlas. esrf. eu / ), enabling download and use of hip - ct data by biomedical researchers across the world. in summary, we have achieved quantitative mapping of the arterial network of an intact human kidney, from renal artery to interlobular arteries, for the first time. this vital step progresses our understanding of how physical properties of the kidney vasculature relate to cellular and molecular heterogeneity, whilst generating key inputs for future biophysical modelling of human kidney vascular physiology. ultimately, we envisage that mapping of microstructural detail will become routine at the scale of the whole kidney, providing a means to link cellular events with organ physiology and pathology. an intact human kidney was obtained from a 63 - year - old male ( cause of death: pancreatic cancer ), who consented to body donation to the laboratoire d ’ anatomie des alpes francaises before death. transport and imaging protocols were approved by the french health ministry. post mortem examination was conducted according to quality appraisal for cadaveric studies scale recommendations. the body was embalmed by injecting 4500 ml of 1. 15 % formalin in lanolin, followed by 1. 44 % formalin, into the right carotid artery, before storage at 3. 6 °c. during evisceration of the right kidney, vessels were exposed, and the surrounding fat and connective tissue were removed. the kidney was post - fixed in 4 % neutral - buffered formaldehyde at room temperature for one week. the kidney was then dehydrate d through an ethanol gra dien t over 9 days to a final equilibrium of 70 %. each solution was four - fold greater than the volume of the organ, and, during dehydration, the solution was degassed using a diaphrag m vacuum pump ( vacuubrand, mv2, 1. 9m / h ) to remove excess dissolved gas. the dehydrate d kidney was transferred to a polyethylene terephthalate jar where it was physically stabilised using a crushed agar - agar ethanol mixture, and then imaged. imaging was performed on the bm05 beamline at the esrf following the hip - ct protocol. initially, the whole kidney was imaged at 25 µm per voxel ( isotropic edge length ). vois within the same kidney were also imaged at 6. 5 and 2. 6 µm per voxel. tomographic reconstruction was performed using the pyhst2 software and following the steps detailed in previous studies. briefly, a filtered back - projection algorithm, with single - distance phase retrieval, coupled to an unsharp mask filter, was applied to the collected radiographs. reconstruction and scanning parameters are provided in supplementary note 1, supplementary tables 1 and 2. the reconstructed volumes were binned ( averaged ) to 50, 13, and 5. 2 µm per voxel, respectively, to increase the signal - to - noise ratio, reduce inter - annotator variability and reduce computational load for subsequent image segmentation and quantification ( see supplementary fig. 1 ). all reconstructed image volumes and metadata can be accessed at human - organ - atlas. esrf. eu. a table for direct doi links for each dataset is provided in supplementary table 2. prior to manual segmentation, images were filtered to enhance blood vessel contrast using amira - avizo ( v2021. 1 ) software. a 3d median filter ( iterations = 2 and 26 neighbourhood analysis ) was used to reduce image noise. image normalisation was performed using background detection correction ( default parameter settings ). a manual segmentation of the arterial networks was performed in amira - avizo using a combination of methodologies. first, a 3d region growing tool was used, where the user selects an initial voxel within a vessel lumen along with set intensity and contrast thresholds. any voxel within the connected neighbourhood of the initially selected voxel with an intensity and contrast within thresholds are added to the region. multiple seeds points and thresholds, as well as manual limits on the region, are used by the annotator to ensure the lumens of all vessels are ac curate ly identified. in areas of collapsed or blood - filled vessels, annotators manually paint lumen voxels utilising three orthogonal views to ensure connection of the vascular network. an annotator continues this process in an iterative fashion by selecting seed points, altering the thresholds and manually correction, resulting in expansion of an interconnected vascular network ( method shown in supplementary movie 3 ). once the first annotator has filled the interior of all vessels, data are passed to a second annotator, who repeats the process, but starting in reverse slice order. a third annotator serves as a proofreader by quantitatively reviewing the labels. the proofreader is presented with 5 – 9 randomised 2d slices of the data within any one of three orthogonal planes. they then count the number of vessels cross - sections present in the slice, recording the true positive and false negative number of vessel cross - sections that have been segmented. the proofreader returns the data to the initial two annotators, highlighting areas where vessels are not identified. this three - annotator process repeats iteratively until the proofreader does not find any false negatives.