AIMC Topic: Kidney

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A deep-learning toolkit for visualization and interpretation of segmented medical images.

Cell reports methods
Generalizability of deep-learning (DL) model performance is not well understood and uses anecdotal assumptions for increasing training data to improve segmentation of medical images. We report statistical methods for visual interpretation of DL model...

High-Throughput, Label-Free and Slide-Free Histological Imaging by Computational Microscopy and Unsupervised Learning.

Advanced science (Weinheim, Baden-Wurttemberg, Germany)
Rapid and high-resolution histological imaging with minimal tissue preparation has long been a challenging and yet captivating medical pursuit. Here, the authors propose a promising and transformative histological imaging method, termed computational...

A neural network for glomerulus classification based on histological images of kidney biopsy.

BMC medical informatics and decision making
BACKGROUND: Computer-aided diagnosis (CAD) systems based on medical images could support physicians in the decision-making process. During the last decades, researchers have proposed CAD systems in several medical domains achieving promising results....

Deep learning identified pathological abnormalities predictive of graft loss in kidney transplant biopsies.

Kidney international
Interstitial fibrosis, tubular atrophy, and inflammation are major contributors to kidney allograft failure. Here we sought an objective, quantitative pathological assessment of these lesions to improve predictive utility and constructed a deep-learn...

Workflow for automatic renal perfusion quantification using ASL-MRI and machine learning.

Magnetic resonance in medicine
PURPOSE: Clinical applicability of renal arterial spin labeling (ASL) MRI is hampered because of time consuming and observer dependent post-processing, including manual segmentation of the cortex to obtain cortical renal blood flow (RBF). Machine lea...

Advanced Kidney Volume Measurement Method Using Ultrasonography with Artificial Intelligence-Based Hybrid Learning in Children.

Sensors (Basel, Switzerland)
In this study, we aimed to develop a new automated method for kidney volume measurement in children using ultrasonography (US) with image pre-processing and hybrid learning and to formulate an equation to calculate the expected kidney volume. The vol...

A Nomogram for the Prediction of Intermediate Significant Renal Function Loss After Robot-assisted Partial Nephrectomy for Localized Renal Tumors: A Prospective Multicenter Observational Study (RECORd2 Project).

European urology focus
BACKGROUND: Robot-assisted partial nephrectomy (RAPN) is increasingly adopted for the treatment of localized renal tumors; however, rates and predictors of significant renal function (RF) loss after RAPN are still poorly investigated, especially at a...