ArticleScientific reports2023
The utility of automatic segmentation of kidney MRI in chronic kidney disease using a 3D convolutional neural network.
Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed, 7 citations in OpenAlex.
- Frugal Learning Methods for Kidney Segmentation in Non-Contrast MRI.Journal of clinical medicine · 2026Article
- Intra- and interobserver variability in renal multiparametric magnetic resonance imaging: T1 mapping, diffusion-weighted imaging, arterial spin labeling, blood oxygen level-dependent and renal artery flow measurements utilizing manual segmentation.Quantitative imaging in medicine and surgery · 2026Article
- 3D Adversarial Segmentation of Kidney-Transplant Across Multiple MRI Sequences Using Probabilistic and Anatomical Priors.Diagnostics (Basel, Switzerland) · 2026Article
- Explainable deep learning for early diagnosis of chronic kidney disease from CT images in Bangladeshi patients.Scientific reports · 2026Article
- The role of texture analysis of T1 weighted images in diagnosis of chronic kidney disease.Scientific reports · 2026Article
- Vision transformer introduces a new vitality to the classification of renal pathology.BMC nephrology · 2024Article
- Three-dimensional convolutional neural network-based classification of chronic kidney disease severity using kidney MRI.Scientific reports · 2024Article
Corrections and comments
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Authors and funding
13 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
We developed a 3D convolutional neural network (CNN)-based automatic kidney segmentation method for patients with chronic kidney disease (CKD) using MRI Dixon-based T1-weighted in-phase (IP)/opposed-phase (OP)/water-only (WO) images. The dataset comprised 100 participants with renal dysfunction (RD; eGFR < 45 mL/min/1.73 m
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Registered trials
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