The Open Kidney Ultrasound Data Set
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Abstract (arXiv)
Ultrasound, because of its low cost, non-ionizing, and non-invasive characteristics, has established itself as a cornerstone radiological examination. Research on ultrasound applications has also expanded, especially with image analysis with machine learning. However, ultrasound data are frequently restricted to closed data sets, with only a few openly available. Despite being a frequently examined organ, the kidney lacks a publicly available ultrasonography data set. The proposed Open Kidney Ultrasound Data Set is the first publicly available set of kidney brightness mode (B-mode) ultrasound data that includes annotations for multi-class semantic segmentation. It is based on data retrospectively collected in a 5-year period from over 500 patients with a mean age of 53.2 +/- 14.7 years, body mass index of 27.0 +/- 5.4 kg/m2, and most common primary diseases being diabetes mellitus, immunoglobulin A (IgA) nephropathy, and hypertension. There are labels for the view and fine-grained manual annotations from two expert sonographers. Notably, this data includes native and transplanted kidneys. Initial bench-marking measurements are performed, demonstrating a state-of-the-art algorithm achieving a Dice Sorenson Coefficient of 0.85 for the kidney capsule. This data set is a high-quality data set, including two sets of expert annotations, with a larger breadth of images than previously available. In increasing access to kidney ultrasound data, future researchers may be able to create novel image analysis techniques for tissue characterization, disease detection, and prognostication.
Key facts. Cited by 18 papers in the map (data through 14 Oct 2026). Builds on 7 of its 33 references that are in the map. First posted on arXiv 14 Jun 2022.
Builds on
7 of 33 references.
References · 7
- 2021The Medical Segmentation Decathloncited by 628
- 2019Causality matters in medical imagingcited by 193
- 2019The VIA Annotation Software for Images, Audio and Videocited by 167
- 2021Common Limitations of Image Processing Metrics: A Picture Storycited by 59
- 2019BIAS: Transparent reporting of biomedical image analysis challengescited by 57
- 2019Machine Learning with Multi-Site Imaging Data: An Empirical Study on the Impact of Scanner Effectscited by 43
- 2018Automatic kidney segmentation in ultrasound images using subsequent boundary distance regression and pixelwise classification networkscited by 5
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Citing papers per year: 2023: 1; 2024: 2; 2025: 10; 2026: 5.
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- 2024UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasetscited by 24
- 2025USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencodingcited by 16
- 2025U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understandingcited by 10
- 2025Revisiting Data Augmentation for Ultrasound Imagescited by 7
- 2025CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learningcited by 6
- 2023TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Researchcited by 3
- 2024UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentationcited by 3
- 2025Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Modelscited by 3
- 2025UMind-VL: A Generalist Ultrasound Vision-Language Model for Unified Grounded Perception and Comprehensive Interpretationcited by 2
- 2026US-JEPA: A Joint Embedding Predictive Architecture for Ultrasoundcited by 2
- 2025Task-Specific Knowledge Distillation from the Vision Foundation Model for Enhanced Medical Image Segmentationcited by 1
- 2026A texture-based framework for foundational ultrasound modelscited by 1
6 more
- 2026UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentationcited by 1
- 2026UltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasoundcited by 1
- 2025Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasoundcited by 0
- 2025UltraUPConvNet: A UPerNet- and ConvNeXt-Based Multi-Task Network for Ultrasound Tissue Segmentation and Disease Predictioncited by 0
- 2025Diagnostic Performance of Universal-Learning Ultrasound AI Across Multiple Organs and Tasks: the UUSIC25 Challengecited by 0
- 2026UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasoundcited by 0
- 2026UltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasound25 Sep 2026
- 2026UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasound23 Sep 2026
- 2026UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation31 Jul 2026
- 2026US-JEPA: A Joint Embedding Predictive Architecture for Ultrasound22 Feb 2026
- 2026A texture-based framework for foundational ultrasound models1 Feb 2026
- 2025Diagnostic Performance of Universal-Learning Ultrasound AI Across Multiple Organs and Tasks: the UUSIC25 Challenge19 Dec 2025
- 2025UMind-VL: A Generalist Ultrasound Vision-Language Model for Unified Grounded Perception and Comprehensive Interpretation27 Nov 2025
- 2025USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencoding27 Oct 2025
- 2025UltraUPConvNet: A UPerNet- and ConvNeXt-Based Multi-Task Network for Ultrasound Tissue Segmentation and Disease Prediction14 Sep 2025
- 2025Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models30 Jun 2025
- 2025Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound30 Jun 2025
- 2025U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding23 May 2025
6 more
- 2025Task-Specific Knowledge Distillation from the Vision Foundation Model for Enhanced Medical Image Segmentation10 Mar 2025
- 2025CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learning7 Mar 2025
- 2025Revisiting Data Augmentation for Ultrasound Images22 Jan 2025
- 2024UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasets25 Nov 2024
- 2024UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation3 Jun 2024
- 2023TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Research19 Oct 2023
- 2025U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understandingcited by 10
- 2025Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Modelscited by 3
- 2025UMind-VL: A Generalist Ultrasound Vision-Language Model for Unified Grounded Perception and Comprehensive Interpretationcited by 2
- 2026UltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasoundcited by 1
- 2026UltraG-Bench: A Multi-task Benchmark for assessing Large Vision-Language Models on Pixel-level Evidence Grounding in Ultrasound25 Sep 2026
- 2025UMind-VL: A Generalist Ultrasound Vision-Language Model for Unified Grounded Perception and Comprehensive Interpretation27 Nov 2025
- 2025Grounding DINO-US-SAM: Text-Prompted Multi-Organ Segmentation in Ultrasound with LoRA-Tuned Vision-Language Models30 Jun 2025
- 2025U2-BENCH: Benchmarking Large Vision-Language Models on Ultrasound Understanding23 May 2025
- 2024UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasetscited by 24
- 2025USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencodingcited by 16
- 2025Revisiting Data Augmentation for Ultrasound Imagescited by 7
- 2025CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learningcited by 6
- 2023TRUSTED: The Paired 3D Transabdominal Ultrasound and CT Human Data for Kidney Segmentation and Registration Researchcited by 3
- 2024UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentationcited by 3
- 2026US-JEPA: A Joint Embedding Predictive Architecture for Ultrasoundcited by 2
- 2026A texture-based framework for foundational ultrasound modelscited by 1
- 2026UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentationcited by 1
- 2025Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasoundcited by 0
- 2025UltraUPConvNet: A UPerNet- and ConvNeXt-Based Multi-Task Network for Ultrasound Tissue Segmentation and Disease Predictioncited by 0
- 2025Diagnostic Performance of Universal-Learning Ultrasound AI Across Multiple Organs and Tasks: the UUSIC25 Challengecited by 0
12 most cited of 13 All 13 (JSON)
- 2026UltraBench 2: Towards Robust Evaluation of Vision Foundation Models on Ultrasound23 Sep 2026
- 2026UltraSAM3: A Concept-Driven Foundation Model for Universal Ultrasound Image Segmentation31 Jul 2026
- 2026US-JEPA: A Joint Embedding Predictive Architecture for Ultrasound22 Feb 2026
- 2026A texture-based framework for foundational ultrasound models1 Feb 2026
- 2025Diagnostic Performance of Universal-Learning Ultrasound AI Across Multiple Organs and Tasks: the UUSIC25 Challenge19 Dec 2025
- 2025USF-MAE: Ultrasound Self-Supervised Foundation Model with Masked Autoencoding27 Oct 2025
- 2025UltraUPConvNet: A UPerNet- and ConvNeXt-Based Multi-Task Network for Ultrasound Tissue Segmentation and Disease Prediction14 Sep 2025
- 2025Deep Learning-Based Semantic Segmentation for Real-Time Kidney Imaging and Measurements with Augmented Reality-Assisted Ultrasound30 Jun 2025
- 2025CACTUS: An Open Dataset and Framework for Automated Cardiac Assessment and Classification of Ultrasound Images Using Deep Transfer Learning7 Mar 2025
- 2025Revisiting Data Augmentation for Ultrasound Images22 Jan 2025
- 2024UltraSam: A Foundation Model for Ultrasound using Large Open-Access Segmentation Datasets25 Nov 2024
- 2024UniUSNet: A Promptable Framework for Universal Ultrasound Disease Prediction and Tissue Segmentation3 Jun 2024
12 newest of 13 All 13 (JSON)