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12 results for “Porcine kidney”
OCT porcine kidney dataset for percutaneous nephrostomy guidance
<h2><strong>Code</strong> [<a href="https://github.com/thepanlab/FOCT_kidney" target="_blank" rel="noopener">GitHub</a>] | <strong>Publication</strong> [<a href="https://doi.org/10.1364/BOE.421299" target="_blank" rel="noopener">Biomedical Optics Express'21</a>]</h2> <h3>Abstract</h3> <p>Percutaneous renal access is the critical initial step in many medical settings. In order to obtain the best surgical outcome with minimum patient morbidity, an improved method for access to the renal calyx is needed. In our study, we built a forward-view optical coherence tomography (OCT) endoscopic system for percutaneous nephrostomy (PCN) guidance. Porcine kidneys were imaged in our experiment to demonstrate the feasibility of the imaging system. Three tissue types of porcine kidneys (renal cortex, medulla, and calyx) can be clearly distinguished due to the morphological and tissue differences from the OCT endoscopic images. To further improve the guidance efficacy and reduce the learning burden of the clinical doctors, a deep-learning-based computer aided diagnosis platform was developed to automatically classify the OCT images by the renal tissue types. Convolutional neural networks (CNN) were developed with labeled OCT images based on the ResNet34, MobileNetv2 and ResNet50 architectures. Nested cross-validation and testing was used to benchmark the classification performance with uncertainty quantification over 10 kidneys, which demonstrated robust performance over substantial biological variability among kidneys. ResNet50-based CNN models achieved an average classification accuracy of 82.6%±3.0%. The classification precisions were 79%±4% for cortex, 85%±6% for medulla, and 91%±5% for calyx and the classification recalls were 68%±11% for cortex, 91%±4% for medulla, and 89%±3% for calyx. Interpretation of the CNN predictions showed the discriminative characteristics in the OCT images of the three renal tissue types. The results validated the technical feasibility of using this novel imaging platform to automatically recognize the images of renal tissue structures ahead of the PCN needle in PCN surgery.</p> <h3>Description</h3> <p>The dataset contains OCT images of 10 porcine kidneys from three tissues: cortex, medulla, and pelvis calyx. There is 1000 images per tissues/per kidney. More information about the dataset can be found in the paper: <a href="https://doi.org/10.1364/BOE.421299">https://doi.org/10.1364/BOE.421299</a></p> <p>The repository that processed this dataset can be found at <a href="https://github.com/thepanlab/FOCT_kidney">https://github.com/thepanlab/FOCT_kidney</a></p> <p> </p>
Porcine Kidney Xenotransplantation in Patients With End-Stage Kidney Disease
ClinicalTrials.gov study NCT05340426. IPD Sharing: NO. Countries: 1. Publications: 1.
Transcription analysis from the human embryonic kidney 293 cells (HEK293) were pre-treated with JIB-04, and then uninfected and infected with porcine rotavirus (PoRV)
GEO Series GSE156219. Homo sapiens. 12 samples. Type: Expression profiling by high throughput sequencing.
Kinetic of gene expression signatures on ischemia porcine kidney
GEO Series GSE109719. Sus scrofa. 40 samples. Type: Expression profiling by array.
Expression data from porcine kidney cell (PK15) transfected by the plasmids
GEO Series GSE71945. Sus scrofa. 60 samples. Type: Expression profiling by array.
Longitudinal RNA-seq of Gene-edited Porcine Kidneys in Cynomolgus Macaques
GEO Series GSE210556. Sus scrofa. 29 samples. Type: Expression profiling by high throughput sequencing.
Endothelial Identity of Porcine Double-sorted CD31+ Kidney Cells
GEO Series GSE211431. Sus scrofa. 5 samples. Type: Expression profiling by high throughput sequencing.
Porcine anti-human lymphocyte immunoglobulin depletes the lymphocyte population to promote successful kidney transplantation
GEO Series GSE226328. Homo sapiens. 2 samples. Type: Expression profiling by high throughput sequencing.
A Porcine Model to Study the Effect of Neurologic Death (ND) on Kidney Genomic Responses
GEO Series GSE94709. Sus scrofa. 20 samples. Type: Expression profiling by array.
scRNA-seq of Gene-edited Porcine Kidneys Prior to Xenotransplantation into Cynomolgus Macaques
GEO Series GSE210557. Sus scrofa. 4 samples. Type: Expression profiling by high throughput sequencing.
Gene expression signatures of ischemia on porcine kidney
GEO Series GSE79418. Sus scrofa. 6 samples. Type: Expression profiling by array.
Conditioning of porcine kidneys during dynamic preservation with exosomes derived from Urine Progenitor Cells
GEO Series GSE255005. Sus scrofa. 17 samples. Type: Expression profiling by high throughput sequencing.
ScienceDex guides
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These curated guides explain access requirements, typical timelines, costs, and reuse considerations for widely used research datasets.
Allen Brain Atlas
Allen Brain Atlas is an Allen Institute collection of brain map atlases, datasets, APIs, and analysis tools covering mouse, human, and non-human primate brain resources.
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DANDI Archive for NWB datasets
DANDI is a BRAIN Initiative archive for publishing and sharing neurophysiology data, including electrophysiology, optophysiology, and behavioral data packaged as NWB and related standards.
International Brain Laboratory public data
The International Brain Laboratory public data releases expose standardized mouse decision-making experiments, including Neuropixels recordings, widefield calcium imaging, behavior, and session metadata accessed through the ONE API.
OpenNeuro
OpenNeuro is a free, open platform for sharing neuroimaging datasets, with public search, dataset pages, and download paths for web, S3, DataLad, and the OpenNeuro CLI.