Table 1.
Kidney-centric artificial intelligence tools
| Publication | Journal | Authors | Year | Tools | Applied Task |
|---|---|---|---|---|---|
| Computational pathology analysis of tissue microarrays predicts survival of renal clear cell carcinoma patients | Lect. Notes Comput. Sc., MICCAI | Fuchs et al. [3] | 2008 | Local Binary Patterns (LBP) Random Forest Survival Analysis | Tissue Microarray (TMA) Analysis Nuclei Detection Prognostication |
| Weakly supervised cell nuclei detection and segmentation on tissue microarrays of renal clear cell carcinoma | Lect. Notes Comput. Sc., DAGM | Fuchs et al. [3] | 2008 | Edge Detection Morphological Image Processing Support Vector Machine (SVM) |
TMA Analysis Nuclei Detection |
| Computational TMA analysis and cell nucleus classification of renal cell carcinoma | Lect. Notes Comput. Sc., DAGM | Schuffler et al. [4] | 2010 | Graph-Cut Optimization Feature Engineering SVM |
TMA Analysis Nuclei Segmentation Nuclei Classification |
| Segmental HOG: new descriptor for glomerulus detection in kidney microscopy image | BMC Bioinformatics | Kato et al. [5] | 2015 | Segmental Histogram of Oriented Gradients SVM |
Glomerulus Detection |
| Unsupervised labelling of glomerular boundaries using Gabor filters and statistical testing in renal histology | J. Med. Imaging | Ginley et al. [6] | 2017 | Gabor Filterbank Statistical Testing |
Glomerulus Segmentation |
| Multiradial LBP features as a tool for rapid glomerular detection and assessment in whole slide histopathology images | Sci. Rep. | Simon et al. [7] | 2018 | Multiradial Colour LBP SVM Convolutional Neural Network (CNN) |
Glomerulus detection Glomerulus subclassification |
| Region-based convolutional neural nets for localization of glomeruli in trichrome-stained whole kidney sections. | J. Am. Soc. Nephrol. | Bukowy et al. [8] | 2018 | Region-based CNN | Glomerulus detection |
| Association of pathological fibrosis with renal survival using deep neural networks | Kidney Int. Reports | Kolachalama et al. [9▪▪] | 2018 | CNN | Prediction of clinical phenotype from trichrome image features |
| Glomerulus classification and detection based on convolutional neural networks | J. Imaging | Gallego et al. [10] | 2018 | CNN | Glomerulus detection |
| Segmentation of glomeruli within trichrome images using deep learning | Kidney Int. Reports | Kannan et al. [11▪▪] | 2019 | CNN | Glomerulus detection Glomerulus classification |
| An integrated iterative annotation technique for easing neural network training in medical image analysis | Nat. Mach. Intell. | Lutnick et al. [12▪] | 2019 | CNN - Semantic segmentation | Glomerulus segmentation Multiclass segmentation of renal morphology |
| Computational segmentation and classification of diabetic glomerulosclerosis | J. Am. Soc. Nephrol. | Ginley et al. [13▪] | 2019 | Feature engineering Recurrent Neural Network (RNN) |
Glomerulus Classification Diabetic nephropathy classification |
| Deep learning-based histopathologic assessment of kidney tissue | J. Am. Soc. Nephrol. | Hermsen et al. [2▪▪] | 2019 | CNN - Semantic segmentation | Multiclass segmentation of renal morphology |
In recent years, the field of renal pathology has seen a surge in the volume of works applying computational image analysis and machine learning for analysis of benign renal histomorphometry.