Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Urinary Tract Calculi III: Medical Management

Urinary Tract Calculi III: Medical Management

The diagnosis of renal calculi involves several imaging techniques, including non-contrast CT scans and ultrasound. These methods help visualize kidney stones, assess their size and location, and detect possible obstructions. Additionally, Measuring urine pH is useful for diagnosing specific stone types, such as struvite (alkaline pH) and uric acid stones (acidic pH). Cystine stones are primarily linked to cystinuria, a genetic condition. A urinalysis helps detect blood in the urine (hematuria)...

Urinary Tract Calculi VI: Surgical Management

Urinary Tract Calculi VI: Surgical Management

Procedures for Kidney StonesMedical intervention is necessary when kidney stones or renal calculi are too large to pass spontaneously (typically greater than 5 millimeters) when stones are accompanied by symptomatic infection (such as fever or pyelonephritis), when they impair kidney function, or when they cause persistent symptoms like severe pain, nausea, or urinary retention. Additionally, patients with only one kidney or those who cannot be treated with medical management also require...

Imaging Studies III: Computed Tomography

Imaging Studies III: Computed Tomography

DefinitionComputed Tomography (CT) of the genitourinary (GU) tract is a non-invasive imaging modality that utilizes X-rays and computer processing to generate detailed cross-sectional images of the urinary system, encompassing the kidneys, ureters, bladder, and adjacent structures such as the adrenal glands.PurposeCT scans of the GU tract serve several diagnostic and therapeutic purposes, including:Diagnosis of Urinary Tract Diseases: Detects kidney stones, tumors, cysts, and congenital...

Urinary Tract Calculi I: Introduction

Urinary Tract Calculi I: Introduction

Renal calculi, or kidney stones, are solid deposits of minerals and salts formed inside the kidneys. In medical terminology, "calculus" refers to the stone itself, while "lithiasis" describes the process of stone formation. Depending on their location within the urinary system, these stones may be classified as either urolithiasis, when situated within the urinary tract, or nephrolithiasis, when located within the kidneys. Each term signifies the specific impact of the stone.Predisposition...

Urinary Tract Calculi V: Nursing Management

Urinary Tract Calculi V: Nursing Management

AssessmentSubjective Data: Obtain a detailed health history, including any recent or chronic urinary tract infections, periods of immobilization, previous episodes of renal calculi, and medical conditions such as gout, benign prostatic hyperplasia, or hyperparathyroidism. Review the medication history for drugs that may influence stone formation, including allopurinol, analgesics, loop diuretics, or thiazide diuretics. Document the use of long-term indwelling catheters and any past surgical...

Imaging Studies V: Intravenous Urography and Retrograde Pyelography

Imaging Studies V: Intravenous Urography and Retrograde Pyelography

IntroductionIntravenous Urography (IVU) and Retrograde Pyelography (RP) are important diagnostic imaging techniques used to evaluate the urinary system. These methods help identify structural abnormalities, obstructions, and functional issues in the kidneys, ureters, and bladder. Both procedures use iodine-based contrast media to enhance the visibility of urinary tract structures on X-ray images, though they differ in their methods and indications.1. Intravenous Urography (IVU)Intravenous...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

Improved coronary CT angiography image quality using photon-counting detector CT in SCAPIS reexamination: scan protocol and comparative analysis.

European journal of radiology·2026

Same author

The acute pulmonary embolism CT protocol should not be optimized for acute aortic syndrome.

European heart journal. Cardiovascular Imaging·2026

Same author

Soft-tissue and half-value windows outperform bone window in ureteral stone size measurements in non-enhanced computed tomography.

Acta radiologica (Stockholm, Sweden : 1987)·2025

Same author

Advancing decision-making in shock wave lithotripsy for upper ureteral stones: the role of radiological stone impaction markers.

Urolithiasis·2025

Same author

No-touch vein grafts in coronary artery bypass surgery: a registry-based randomized clinical trial.

European heart journal·2025

Same author

Immunomodulatory treatment may change functional and structural brain imaging in severe mental disorders.

Brain, behavior, & immunity - health·2024

Search research articles

Related Experiment Video

Updated: May 26, 2026

Estimation of Urinary Nanocrystals in Humans using Calcium Fluorophore Labeling and Nanoparticle Tracking Analysis

Estimation of Urinary Nanocrystals in Humans using Calcium Fluorophore Labeling and Nanoparticle Tracking Analysis

Published on: February 9, 2021

Urinary stone size estimation: a new segmentation algorithm-based CT method.

Mats Lidén¹, Torbjörn Andersson, Mathias Broxvall

¹School of Health and Medical Sciences, Örebro University, S-701 82, Örebro, Sweden. matsliden@yahoo.com

European Radiology

|December 14, 2011

Summary

A new algorithm for estimating urinary calculus size from CT images reduces reader variability. This computer-aided method shows excellent agreement with manual estimations, improving treatment decisions for renal colic.

More Related Videos

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Published on: March 14, 2018

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Related Experiment Videos

Last Updated: May 26, 2026

Estimation of Urinary Nanocrystals in Humans using Calcium Fluorophore Labeling and Nanoparticle Tracking Analysis

Estimation of Urinary Nanocrystals in Humans using Calcium Fluorophore Labeling and Nanoparticle Tracking Analysis

Published on: February 9, 2021

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Outer-Boundary Assisted Segmentation and Quantification of Trabecular Bones by an Imagej Plugin

Published on: March 14, 2018

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Automated Joint Space Detection Improves Bone Segmentation Accuracy

Published on: November 28, 2025

Area of Science:

Medical Imaging
Radiology
Digital Image Processing

Background:

Accurate size estimation of ureteral calculi in CT images is crucial for managing renal colic.
Manual size estimation by radiologists can exhibit inter-reader variability.

Purpose of the Study:

To develop a reader-independent algorithm for segmenting and estimating the size of urinary calculi in CT scans.
To validate the algorithm's performance against manual size estimations by multiple readers.

Main Methods:

A segmentation algorithm combining interpolated zoom, binary thresholding, and morphological operations was developed.
The algorithm was optimized using 10 CT examinations and validated on 40 others.
Calculus sizes were compared against the mean estimations of 11 independent readers.

Main Results:

The developed algorithm demonstrated minimal bias (0.0 mm) and a low standard deviation of difference (0.26 mm) compared to the mean reader estimations.
Bland-Altman analysis showed narrow limits of agreement (0.0 ± 0.5 mm).

Conclusions:

The reader-independent algorithm for urinary calculus size estimation shows strong agreement with expert manual estimations.
This automated approach reduces inter-reader variability, potentially leading to more consistent and reliable data for treatment planning.