AI applications in renal pathology

Y Huo, R Deng, Q Liu, AB Fogo, H Yang - Kidney international, 2021 - Elsevier
The explosive growth of artificial intelligence (AI) technologies, especially deep learning
methods, has been translated at revolutionary speed to efforts in AI-assisted healthcare …

Artificial intelligence-assisted renal pathology: advances and prospects

Y Wang, Q Wen, L Jin, W Chen - Journal of Clinical Medicine, 2022 - mdpi.com
Digital imaging and advanced microscopy play a pivotal role in the diagnosis of kidney
diseases. In recent years, great achievements have been made in digital imaging, providing …

Glomerulosclerosis identification in whole slide images using semantic segmentation

G Bueno, MM Fernandez-Carrobles… - Computer methods and …, 2020 - Elsevier
Abstract Background and Objective: Glomeruli identification, ie, detection and
characterization, is a key procedure in many nephropathology studies. In this paper …

Deep learning global glomerulosclerosis in transplant kidney frozen sections

JN Marsh, MK Matlock, S Kudose… - IEEE transactions on …, 2018 - ieeexplore.ieee.org
Transplantable kidneys are in very limited supply. Accurate viability assessment prior to
transplantation could minimize organ discard. Rapid and accurate evaluation of intra …

Classification of glomerular pathological findings using deep learning and nephrologist–AI collective intelligence approach

E Uchino, K Suzuki, N Sato, R Kojima… - International journal of …, 2020 - Elsevier
Background Automated classification of glomerular pathological findings is potentially
beneficial in establishing an efficient and objective diagnosis in renal pathology. While …

Identification of glomerular lesions and intrinsic glomerular cell types in kidney diseases via deep learning

C Zeng, Y Nan, F Xu, Q Lei, F Li, T Chen… - The Journal of …, 2020 - Wiley Online Library
Identification of glomerular lesions and structures is a key point for pathological diagnosis,
treatment instructions, and prognosis evaluation in kidney diseases. These time‐consuming …

Classification of glomerular hypercellularity using convolutional features and support vector machine

P Chagas, L Souza, I Araújo, N Aldeman… - Artificial intelligence in …, 2020 - Elsevier
Glomeruli are histological structures of the kidney cortex formed by interwoven blood
capillaries, and are responsible for blood filtration. Glomerular lesions impair kidney filtration …

[HTML][HTML] A deep learning-based approach for glomeruli instance segmentation from multistained renal biopsy pathologic images

L Jiang, W Chen, B Dong, K Mei, C Zhu, J Liu… - The American Journal of …, 2021 - Elsevier
Glomeruli instance segmentation from pathologic images is a fundamental step in the
automatic analysis of renal biopsies. Glomerular histologic manifestations vary widely …

[HTML][HTML] Glomerular disease classification and lesion identification by machine learning

CK Yang, CY Lee, HS Wang, SC Huang, PI Liang… - biomedical …, 2022 - Elsevier
Background Classification of glomerular diseases and identification of glomerular lesions
require careful morphological examination by experienced nephropathologists, which is …

[HTML][HTML] A U-Net based framework to quantify glomerulosclerosis in digitized PAS and H&E stained human tissues

J Gallego, Z Swiderska-Chadaj, T Markiewicz… - … Medical Imaging and …, 2021 - Elsevier
Reliable counting of glomeruli and evaluation of glomerulosclerosis in renal specimens are
essential steps to assess morphological changes in kidney and identify individuals requiring …