Morning urine samples of patients with IgA nephropathy, idiopathic membranous nephropathy, diabetic nephropathy, and minimal degenerative nephropathy confirmed by renal needle biopsy in our hospital from November 2020 to January 2022 were collected. By scanning the morning urine samples of corresponding patients with microhyperspectral imager, machine learning and deep learning were used to classify microhyperspectral images, and the classification accuracy was greater than 85%. Thus, hyperspectral imaging technology could be used as a non-invasive diagnostic means to assist the diagnosis of glomerular diseases.
Study Type
OBSERVATIONAL
Enrollment
80
Microscopic hyperspectral imaging system
Microhyperspectral image of urine specimen
Microhyperspectral images of urine samples from patients with four different glomerular diseases before treatment
Time frame: 2023.4-2023.10
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