AIMC Topic: Kidney

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MuRCL: Multi-Instance Reinforcement Contrastive Learning for Whole Slide Image Classification.

IEEE transactions on medical imaging
Multi-instance learning (MIL) is widely adop- ted for automatic whole slide image (WSI) analysis and it usually consists of two stages, i.e., instance feature extraction and feature aggregation. However, due to the "weak supervision" of slide-level l...

Three-dimensional Virtual Models of the Kidney with Colored Perfusion Regions: A New Algorithm-based Tool for Optimizing the Clamping Strategy During Robot-assisted Partial Nephrectomy.

European urology
BACKGROUND: An empirical selective clamping strategy based on the direction of the arterial branches can lead to failures during partial nephrectomy, even when assisted by three-dimensional virtual models (3DVMs).

High-throughput image analysis with deep learning captures heterogeneity and spatial relationships after kidney injury.

Scientific reports
Recovery from acute kidney injury can vary widely in patients and in animal models. Immunofluorescence staining can provide spatial information about heterogeneous injury responses, but often only a fraction of stained tissue is analyzed. Deep learni...

A novel multiplex score to predict outcomes of partial nephrectomy for multiple tumors.

Urologic oncology
BACKGROUND: The RENAL nephrometry score (RNS) is widely used to describe renal mass complexity and inform patient counseling for partial nephrectomy (PN). However, in cases with multiple tumors, it is unknown which features drive perioperative outcom...

A novel dataset and efficient deep learning framework for automated grading of renal cell carcinoma from kidney histopathology images.

Scientific reports
Trends of kidney cancer cases worldwide are expected to increase persistently and this inspires the modification of the traditional diagnosis system to respond to future challenges. Renal Cell Carcinoma (RCC) is the most common kidney cancer and resp...

Glomerulus Detection Using Segmentation Neural Networks.

Journal of digital imaging
Digital pathology is vital for the correct diagnosis of kidney before transplantation or kidney disease identification. One of the key challenges in kidney diagnosis is glomerulus detection in kidney tissue segments. In this study, we propose a deep ...

Acquisition time reduction in pediatric Tc-DMSA planar imaging using deep learning.

Journal of applied clinical medical physics
PURPOSE: Given the potential risk of motion artifacts, acquisition time reduction is desirable in pediatric Tc-dimercaptosuccinic acid (DMSA) scintigraphy. The aim of this study was to evaluate the performance of predicted full-acquisition-time imag...

Robot-assisted pyeloplasty for ureteropelvic junction obstruction in renal anomalies.

Journal of pediatric urology
The surgical video demonstrates the technical nuances of performing pyeloplasties on complex renal anomalies, including duplex, horseshoe, malrotated, and ectopic kidneys. The video also highlights the anatomic relationships of the affected kidney fo...

Deep learning-based segmentation and quantification of podocyte foot process morphology suggests differential patterns of foot process effacement across kidney pathologies.

Kidney international
Morphological alterations at the kidney filtration barrier increase intrinsic capillary wall permeability resulting in albuminuria. However, automated, quantitative assessment of these morphological changes has not been possible with electron or ligh...