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1,018 results on '"Dahl, Anders"'

52. Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species

Author

Kjer, Hans Martin, primary, Andersson, Mariam, additional, He, Yi, additional, Pacureanu, Alexandra, additional, Daducci, Alessandro, additional, Pizzolato, Marco, additional, Salditt, Tim, additional, Robisch, Anna-Lena, additional, Eckermann, Marina, additional, Toepperwien, Mareike, additional, Dahl, Anders Bjorholm, additional, Elkjær, Maria Louise, additional, Illes, Zsolt, additional, Ptito, Maurice, additional, Dahl, Vedrana Andersen, additional, and Dyrby, Tim B., additional

Published
2024
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53. Assessment of algorithms for mitosis detection in breast cancer histopathology images

Author

Veta, Mitko, van Diest, Paul J., Willems, Stefan M., Wang, Haibo, Madabhushi, Anant, Cruz-Roa, Angel, Gonzalez, Fabio, Larsen, Anders B. L., Vestergaard, Jacob S., Dahl, Anders B., Cireşan, Dan C., Schmidhuber, Jürgen, Giusti, Alessandro, Gambardella, Luca M., Tek, F. Boray, Walter, Thomas, Wang, Ching-Wei, Kondo, Satoshi, Matuszewski, Bogdan J., Precioso, Frederic, Snell, Violet, Kittler, Josef, de Campos, Teofilo E., Khan, Adnan M., Rajpoot, Nasir M., Arkoumani, Evdokia, Lacle, Miangela M., Viergever, Max A., and Pluim, Josien P. W.

Subjects
Computer Science - Computer Vision and Pattern Recognition
Abstract

The proliferative activity of breast tumors, which is routinely estimated by counting of mitotic figures in hematoxylin and eosin stained histology sections, is considered to be one of the most important prognostic markers. However, mitosis counting is laborious, subjective and may suffer from low inter-observer agreement. With the wider acceptance of whole slide images in pathology labs, automatic image analysis has been proposed as a potential solution for these issues. In this paper, the results from the Assessment of Mitosis Detection Algorithms 2013 (AMIDA13) challenge are described. The challenge was based on a data set consisting of 12 training and 11 testing subjects, with more than one thousand annotated mitotic figures by multiple observers. Short descriptions and results from the evaluation of eleven methods are presented. The top performing method has an error rate that is comparable to the inter-observer agreement among pathologists., Comment: 23 pages, 5 figures, accepted for publication in the journal Medical Image Analysis

Published
2014
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54. Super Resolution Ultrasound Imaging Using the Erythrocytes:II: Velocity Images

Author

Naji, Mostafa Amin, Taghavi, Iman, Schou, Mikkel, Praesius, Sebastian Kazmarek, Hansen, Lauge Naur, Panduro, Nathalie Sarup, Andersen, Sofie Bech, Sogaard, Stinne Byrholdt, Gundlach, Carsten, Kjer, Hans Martin, Tomov, Borislav Gueorguiev, Thomsen, Erik Vilain, Nielsen, Michael Bachmann, Larsen, Niels Bent, Dahl, Anders Bjorholm, Sorensen, Charlotte Mehlin, Jensen, Jorgen Arendt, Naji, Mostafa Amin, Taghavi, Iman, Schou, Mikkel, Praesius, Sebastian Kazmarek, Hansen, Lauge Naur, Panduro, Nathalie Sarup, Andersen, Sofie Bech, Sogaard, Stinne Byrholdt, Gundlach, Carsten, Kjer, Hans Martin, Tomov, Borislav Gueorguiev, Thomsen, Erik Vilain, Nielsen, Michael Bachmann, Larsen, Niels Bent, Dahl, Anders Bjorholm, Sorensen, Charlotte Mehlin, and Jensen, Jorgen Arendt

Published
2024

55. Super Resolution Ultrasound Imaging using the Erythrocytes:I: Density Images

Author

Jensen, Jørgen Arendt, Naji, Mostafa Amin, Praesius, Sebastian Kazmarek, Taghavi, Iman, Schou, Mikkel, Hansen, Lauge Naur, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Panduro, Nathalie Sarup, Sørensen, Charlotte Mehlin, Nielsen, Michael Bachmann, Gundlach, Carsten, Kjer, Hans Martin, Dahl, Anders Bjorholm, Tomov, Borislav Gueorguiev, Ommen, Martin Lind, Larsen, Niels Bent, Thomsen, Erik Vilain, Jensen, Jørgen Arendt, Naji, Mostafa Amin, Praesius, Sebastian Kazmarek, Taghavi, Iman, Schou, Mikkel, Hansen, Lauge Naur, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Panduro, Nathalie Sarup, Sørensen, Charlotte Mehlin, Nielsen, Michael Bachmann, Gundlach, Carsten, Kjer, Hans Martin, Dahl, Anders Bjorholm, Tomov, Borislav Gueorguiev, Ommen, Martin Lind, Larsen, Niels Bent, and Thomsen, Erik Vilain

Published
2024

56. HyperLeaf2024 - A Hyperspectral Imaging Dataset for Classification and Regression of Wheat Leaves

Author

Laprade, William Michael, Pieta, Pawel, Kutuzova, Svetlana, Westergaard, Jesper Cairo, Nielsen, Mads, Christensen, Svend, Dahl, Anders Bjorholm, Laprade, William Michael, Pieta, Pawel, Kutuzova, Svetlana, Westergaard, Jesper Cairo, Nielsen, Mads, Christensen, Svend, and Dahl, Anders Bjorholm

Abstract

Hyperspectral imaging is a widely used method in remote sensing, particularly for use in airborne and satellite-based land surveillance. Its versatility is, however, much larger and has also seen usage in everything ranging from food processing and surveillance to astronomy and waste sorting. It is also gaining inroads with agricultural research. With most available datasets focusing on per-pixel classification, there is, however, a potential for hyperspectral whole-image analysis, but there is a severe lack of datasets for whole-image analysis. To help fill this gap and facilitate methodological development in whole-image hyperspectral image analysis, we introduce the Hy-perLeaf2024 dataset. The dataset consists of 2410 hyper-spectral images of wheat leaves, along with associated classification and regression targets at both the leaf level and the plot level. In addition to the dataset, we also provide experiments showing the importance of pretraining and highlighting the future research direction in whole-image hyper-spectral image analysis.

Published
2024

57. Superresolution of Real-World Multiscale Bone CT Verified with Clinical Bone Measures

Author

Yap, Moi Hoon, Kendrick, Connah, Behera, Ardhendu, Cootes, Timothy, Zwiggelaar, Reyer, Bardenfleth, Sophia W., Dahl, Vedrana A., Villa, Chiara, Kazakia, Galateia, Dahl, Anders B., Yap, Moi Hoon, Kendrick, Connah, Behera, Ardhendu, Cootes, Timothy, Zwiggelaar, Reyer, Bardenfleth, Sophia W., Dahl, Vedrana A., Villa, Chiara, Kazakia, Galateia, and Dahl, Anders B.

Abstract

Medical image superresolution models are typically trained on synthetic low-resolution/high-resolution image pairs. This is easier and does not reflect the real-world challenge of learning superresolution for clinical CT scans from micro-CT. Furthermore, most medical image superresolution models are evaluated using standard image similarity metrics like Peak-Signal-to-Noise-Ratio (PSNR) and Structural Similarity Index Measure (SSIM), even though it is well known, that they favor image characteristics that are not suitable in a medical image setting. In this paper, we investigate how training on real or synthetic data affects model performance. We also evaluate how models perform, when using measures that are relevant for clinical bone analysis. We train two well-established superresolution models, SRGAN and ESRGAN on two real-world multiscale human bone CT datasets. We compare this approach with training the models on synthetic data, where low-resolution images are produced by subsampling and blurring high-resolution images, as is the common approach when assessing superresolution architectures for medical images. When evaluating performance, we calculate both clinically relevant bone measures, Bone Volume Fraction, Thickness and Degree of Anisotropy as well as PSNR and SSIM. We find that training on real data generally makes the model perform worse than when training on synthetic data. This suggests that more can be learned from using real-world data when exploring medical image superresolution. It also seems that the similarity metrics do not always align with the bone measures in terms of lowest error, indicating that including the bone measures in our evaluation gives a fuller picture of how our models perform.

Published
2024

58. FibreTracker: Open-source 3D Python Tool for Fibre Tracking

Author

Binetruy, Christophe, Jacquemin, Frédéric, Pooja, Kumari, Mikkelsen, Lars P., Dahl, Anders B., Dahl, Vedrana A., Binetruy, Christophe, Jacquemin, Frédéric, Pooja, Kumari, Mikkelsen, Lars P., Dahl, Anders B., and Dahl, Vedrana A.

Abstract

FibreTracker is a Python-based interactive tool for tracking individual fibres in a 3D volume. The package contains functions that can detect fibre centres in each slice and the detected centres can be visualized interactively over slices using a slider attached to the visualizer. Once centres are detected, the function can track individual fibres across the volume for characterizing fibre microstructure in the composite. FibreTracker follows two steps; fibre detection detects a peak for each fibre and using the coordinate of those peaks, fibres are tracked by connecting the detected point in each slice. The FibreTracker tool is a user-friendly tool that requires few inputs from the user and comes with a Jupyter notebook for use-case examples, and documentation of the package documentation. Moreover, the method is robust to noise, computationally efficient, and requires no annotation or training. It can track fibres of different scan qualities even when fibre boundaries are not visible. Overall, this tool provides a simple and accessible approach to image-based characterization of fibrous materials.

Published
2024

59. Super Resolution Ultrasound Imaging using the Erythrocytes: I: Density Images

Author

Jensen, Jørgen Arendt, Naji, Mostafa Amin, Praesius, Sebastian Kazmarek, Taghavi, Iman, Schou, Mikkel, Hansen, Lauge Naur, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Panduro, Nathalie Sarup, Sørensen, Charlotte Mehlin, Nielsen, Michael Bachmann, Gundlach, Carsten, Kjer, Hans Martin, Dahl, Anders Bjørholm, Tomov, Borislav Gueorguiev, Ommen, Martin Lind, Larsen, Niels Bent, Thomsen, Erik Vilain, Jensen, Jørgen Arendt, Naji, Mostafa Amin, Praesius, Sebastian Kazmarek, Taghavi, Iman, Schou, Mikkel, Hansen, Lauge Naur, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Panduro, Nathalie Sarup, Sørensen, Charlotte Mehlin, Nielsen, Michael Bachmann, Gundlach, Carsten, Kjer, Hans Martin, Dahl, Anders Bjørholm, Tomov, Borislav Gueorguiev, Ommen, Martin Lind, Larsen, Niels Bent, and Thomsen, Erik Vilain

Published
2024

60. Super Resolution Ultrasound Imaging Using the Erythrocytes: II: Velocity Images

Author

Naji, Mostafa Amin, Taghavi, Iman, Schou, Mikkel, Praesius, Sebastian Kazmarek, Hansen, Lauge Naur, Panduro, Nathalie Sarup, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Gundlach, Carsten, Kjer, Hans Martin, Tomov, Borislav Gueorguiev, Thomsen, Erik Vilain, Nielsen, Michael Bachmann, Larsen, Niels Bent, Dahl, Anders Bjorholm, Sørensen, Charlotte Mehlin, Jensen, Jørgen Arendt, Naji, Mostafa Amin, Taghavi, Iman, Schou, Mikkel, Praesius, Sebastian Kazmarek, Hansen, Lauge Naur, Panduro, Nathalie Sarup, Andersen, Sofie Bech, Søgaard, Stinne Byrholdt, Gundlach, Carsten, Kjer, Hans Martin, Tomov, Borislav Gueorguiev, Thomsen, Erik Vilain, Nielsen, Michael Bachmann, Larsen, Niels Bent, Dahl, Anders Bjorholm, Sørensen, Charlotte Mehlin, and Jensen, Jørgen Arendt

Published
2024

62. Global Similarity with Additive Smoothness for Spectral Segmentation

Author

Dahl, Vedrana Andersen, Dahl, Anders Bjorholm, Hutchison, David, Editorial Board Member, Kanade, Takeo, Editorial Board Member, Kittler, Josef, Editorial Board Member, Kleinberg, Jon M., Editorial Board Member, Mattern, Friedemann, Editorial Board Member, Mitchell, John C., Editorial Board Member, Naor, Moni, Editorial Board Member, Pandu Rangan, C., Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Terzopoulos, Demetri, Editorial Board Member, Tygar, Doug, Editorial Board Member, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Lellmann, Jan, editor, Burger, Martin, editor, and Modersitzki, Jan, editor

Published
2019
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63. Using a Robotic Arm for Measuring BRDFs

Author

Lyngby, Rasmus Ahrenkiel, Matthiassen, Jannik Boll, Frisvad, Jeppe Revall, Dahl, Anders Bjorholm, Aanæs, Henrik, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Felsberg, Michael, editor, Forssén, Per-Erik, editor, Sintorn, Ida-Maria, editor, and Unger, Jonas, editor

Published
2019
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64. Video Frame Interpolation via Cyclic Fine-Tuning and Asymmetric Reverse Flow

Author

Hannemose, Morten, Jensen, Janus Nørtoft, Einarsson, Gudmundur, Wilm, Jakob, Dahl, Anders Bjorholm, Frisvad, Jeppe Revall, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Felsberg, Michael, editor, Forssén, Per-Erik, editor, Sintorn, Ida-Maria, editor, and Unger, Jonas, editor

Published
2019
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65. Material-Based Segmentation of Objects

Author

Stets, Jonathan Dyssel, Lyngby, Rasmus Ahrenkiel, Frisvad, Jeppe Revall, Dahl, Anders Bjorholm, Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Felsberg, Michael, editor, Forssén, Per-Erik, editor, Sintorn, Ida-Maria, editor, and Unger, Jonas, editor

Published
2019
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66. Zonohedral Approximation of Spherical Structuring Element for Volumetric Morphology

Author

Jensen, Patrick M., Trinderup, Camilla H., Dahl, Anders B., Dahl, Vedrana A., Goos, Gerhard, Founding Editor, Hartmanis, Juris, Founding Editor, Bertino, Elisa, Editorial Board Member, Gao, Wen, Editorial Board Member, Steffen, Bernhard, Editorial Board Member, Woeginger, Gerhard, Editorial Board Member, Yung, Moti, Editorial Board Member, Felsberg, Michael, editor, Forssén, Per-Erik, editor, Sintorn, Ida-Maria, editor, and Unger, Jonas, editor

Published
2019
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71. A Probabilistic Framework for Curve Evolution

Author

Dahl, Vedrana Andersen, Dahl, Anders Bjorholm, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Lauze, François, editor, Dong, Yiqiu, editor, and Dahl, Anders Bjorholm, editor

Published
2017
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72. Structure-function analysis of time-resolved immunological phases in metabolic dysfunction- associated fatty liver disease

Author

Schmidt-Christensen, Anja, primary, Eriksson, Gustaw, additional, Laprade, William M., additional, Pirzamanbein, Behnaz, additional, Hörnberg, Maria, additional, Linde, Kajsa, additional, Nilsson, Julia, additional, Skarsfeldt, Mark, additional, Leeming, Diana J., additional, Mokso, Rajmund, additional, Verezhak, Mariana, additional, Dahl, Anders, additional, Dahl, Vedrana, additional, Önnerhag, Kristina, additional, Oghazi, Massoud Rezaee, additional, Mayans, Sofia, additional, and Holmberg, Dan, additional

Published
2024
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73. Super Resolution Ultrasound Imaging Using the Erythrocytes: II: Velocity Images

Author

Naji, Mostafa Amin, primary, Taghavi, Iman, additional, Schou, Mikkel, additional, Præsius, Sebastian Kazmarek, additional, Hansen, Lauge Naur, additional, Panduro, Nathalie Sarup, additional, Andersen, Sofie Bech, additional, Søgaard, Stinne Byrholdt, additional, Gundlach, Carsten, additional, Kjer, Hans Martin, additional, Tomov, Borislav Gueorguiev, additional, Thomsen, Erik Vilain, additional, Nielsen, Michael Bachmann, additional, Larsen, Niels Bent, additional, Dahl, Anders Bjorholm, additional, Sørensen, Charlotte Mehlin, additional, and Jensen, Jorgen Arendt, additional

Published
2024
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74. Super Resolution Ultrasound Imaging using the Erythrocytes: I: Density Images

Author

Jensen, Jørgen Arendt, primary, Naji, Mostafa Amin, additional, Præsius, Sebastian Kazmarek, additional, Taghavi, Iman, additional, Schou, Mikkel, additional, Hansen, Lauge Naur, additional, Andersen, Sofie Bech, additional, Søgaard, Stinne Byrholdt, additional, Panduro, Nathalie Sarup, additional, Sørensen, Charlotte Mehlin, additional, Nielsen, Michael Bachmann, additional, Gundlach, Carsten, additional, Kjer, Hans Martin, additional, Dahl, Anders Bjorholm, additional, Tomov, Borislav Gueorguiev, additional, Ommen, Martin Lind, additional, Larsen, Niels Bent, additional, and Thomsen, Erik Vilain, additional

Published
2024
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87. Development of a New Fractal Algorithm to Predict Quality Traits of MRI Loins

Author

Caballero, Daniel, Caro, Andrés, Amigo, José Manuel, Dahl, Anders B., Ersbøll, Bjarne K., Pérez-Palacios, Trinidad, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Felsberg, Michael, editor, Heyden, Anders, editor, and Krüger, Norbert, editor

Published
2017
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88. Foreign Object Detection in Multispectral X-ray Images of Food Items Using Sparse Discriminant Analysis

Author

Einarsson, Gudmundur, Jensen, Janus N., Paulsen, Rasmus R., Einarsdottir, Hildur, Ersbøll, Bjarne K., Dahl, Anders B., Christensen, Lars Bager, Hutchison, David, Series editor, Kanade, Takeo, Series editor, Kittler, Josef, Series editor, Kleinberg, Jon M., Series editor, Mattern, Friedemann, Series editor, Mitchell, John C., Series editor, Naor, Moni, Series editor, Pandu Rangan, C., Series editor, Steffen, Bernhard, Series editor, Terzopoulos, Demetri, Series editor, Tygar, Doug, Series editor, Weikum, Gerhard, Series editor, Sharma, Puneet, editor, and Bianchi, Filippo Maria, editor

Published
2017
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91. Bridging the 3D geometrical organisation of white matter pathways across anatomical length scales and species

Author

Kjer, Martin, primary, Andersson, Mariam, additional, He, Yi, additional, Pacureanu, Alexandra, additional, Daducci, Alessandro, additional, Pizzolato, Marco, additional, Salditt, Tim, additional, Robisch, Anna-Lena, additional, Eckermann, Marina, additional, Töpperwien, Mareike, additional, Dahl, Anders Bjorholm, additional, Elkjær, Maria Louise, additional, Illes, Zsolt, additional, Ptito, Maurice, additional, Andersen Dahl, Vedrana, additional, and Dyrby, Tim B., additional

Published
2023
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92. Super-Resolution Ultrasound Imaging Using the Erythrocytes—Part I: Density Images

Author

Arendt Jensen, Jorgen, Amin Naji, Mostafa, Kazmarek PraeSius, Sebastian, Taghavi, Iman, Schou, Mikkel, Naur Hansen, Lauge, Bech Andersen, Sofie, Byrholdt Sogaard, Stinne, Sarup Panduro, Nathalie, Mehlin Sorensen, Charlotte, Bachmann Nielsen, Michael, Gundlach, Carsten, Martin Kjer, Hans, Bjorholm Dahl, Anders, Gueorguiev Tomov, Borislav, Lind Ommen, Martin, Bent Larsen, Niels, and Vilain Thomsen, Erik

Abstract

A new approach for vascular super-resolution (SR) imaging using the erythrocytes as targets (SUper-Resolution ultrasound imaging of Erythrocytes (SURE) imaging) is described and investigated. SURE imaging does not require fragile contrast agent bubbles, making it possible to use the maximum allowable mechanical index (MI) for ultrasound scanning for an increased penetration depth. A synthetic aperture (SA) ultrasound sequence was employed with 12 virtual sources (VSs) using a 10-MHz GE L8-18i-D linear array hockey stick probe. The axial resolution was ${1.20}\lambda ~\text {(185.0}~\mu $ m) and the lateral resolution was ${1.50}\lambda ~\text {(231.3}~\mu $ m). Field IIpro simulations were conducted on 12.5- $\mu $ m radius vessel pairs with varying separations. A vessel pair with a separation of $70~\mu $ m could be resolved, indicating a SURE image resolution below half a wavelength. A Verasonics research scanner was used for the in vivo experiments to scan the kidneys of Sprague-Dawley rats for up to 46 s to visualize their microvasculature by processing from 0.1 up to 45 s of data for SURE imaging and for 46.8 s for SR imaging with a SonoVue contrast agent. Afterward, the renal vasculature was filled with the ex vivo micro-computed tomography (CT) contrast agent Microfil, excised, and scanned in a micro-CT scanner at both a 22.6- $\mu $ m voxel size for 11 h and for 20 h in a 5- $\mu $ m voxel size for validating the SURE images. Comparing the SURE and micro-CT images revealed that vessels with a diameter of $28~\mu $ m, five times smaller than the ultrasound wavelength, could be detected, and the dense grid of microvessels in the full kidney was shown for scan times between 1 and 10 s. The vessel structure in the cortex was also similar to the SURE and SR images. Fourier ring correlation (FRC) indicated a resolution capability of $29~\mu $ m. SURE images are acquired in seconds rather than minutes without any patient preparation or contrast injection, making the method translatable to clinical use.

Published
2024
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93. Super-Resolution Ultrasound Imaging Using the Erythrocytes—Part II: Velocity Images

Author

Naji, Mostafa Amin, Taghavi, Iman, Schou, Mikkel, Praesius, Sebastian Kazmarek, Hansen, Lauge Naur, Panduro, Nathalie Sarup, Andersen, Sofie Bech, Sogaard, Stinne Byrholdt, Gundlach, Carsten, Kjer, Hans Martin, Tomov, Borislav Gueorguiev, Thomsen, Erik Vilain, Nielsen, Michael Bachmann, Larsen, Niels Bent, Dahl, Anders Bjorholm, Sorensen, Charlotte Mehlin, and Jensen, Jorgen Arendt

Abstract

Super-resolution ultrasound imaging using the erythrocytes (SURE) has recently been introduced. The method uses erythrocytes as targets instead of fragile microbubbles (MBs). The abundance of erythrocyte scatterers makes it possible to acquire SURE data in just a few seconds compared with several minutes in ultrasound localization microscopy (ULM) using MBs. A high number of scatterers can reduce the acquisition time; however, the tracking of uncorrelated and high-density scatterers is quite challenging. This article hypothesizes that it is possible to detect and track erythrocytes as targets to obtain vascular flow images. A SURE tracking pipeline is used with modules for beamforming, recursive synthetic aperture (SA) imaging, motion estimation, echo canceling, peak detection, and recursive nearest-neighbor (NN) tracker. The SURE tracking pipeline is capable of distinguishing the flow direction and separating tubes of a simulated Field II phantom with 125–25- $\mu \text { m}$ wall-to-wall tube distances, as well as a 3-D printed hydrogel micr-flow phantom with 100–60- $\mu \text { m}$ wall-to-wall channel distances. The comparison of an in vivo SURE scan of a Sprague-Dawley rat kidney with ULM and micro-computed tomography (CT) scans with voxel sizes of 26.5 and $5~\mu \text { m}$ demonstrated consistent findings. A microvascular structure composed of 16 vessels exhibited similarities across all imaging modalities. The flow direction and velocity profiles in the SURE scan were found to be concordant with those from ULM.

Published
2024
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