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Imaging Studies I: Kidney, Ureter, and Bladder Studies

Imaging Studies I: Kidney, Ureter, and Bladder Studies

Kidney, Ureter, and Bladder (KUB) StudiesKidney, Ureter, and Bladder (KUB) studies are standard diagnostic imaging procedures used to assess the anatomy of the urinary system. They are commonly utilized for patients experiencing abdominal pain or urinary symptoms. By using a simple X-ray of the abdomen, KUB studies can reveal structural and pathological abnormalities within the kidneys, ureters, and bladder. These studies are particularly valuable in diagnosing kidney stones, urinary...

Imaging Studies VI: Voiding Cystourethrography and Cystography

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Voiding Cystourethrography (VCUG) and Cystography are specialized radiographic procedures used to examine the structure and function of the bladder and urethra.Voiding Cystourethrography (VCUG)A Voiding Cystourethrogram (VCUG) is a diagnostic imaging procedure that assesses the anatomy and function of the lower urinary tract. It focuses on the bladder, bladder neck, and urethra, helping detect abnormalities such as vesicoureteral reflux (VUR)—the backward or reverse flow of urine into the...

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...

Imaging Studies IV: Magnetic Resonance Imaging

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Introduction:Magnetic Resonance Imaging, or MRI, can include a specialized imaging technique of the urinary system known as Magnetic Resonance Urography (MRU). This radiation-free technique uses strong magnetic fields and radio waves to produce detailed images with the help of a computer. MRU is particularly effective for visualizing fluid-filled structures like the kidneys, ureters, and bladder.Applications of MRI in the Genitourinary SystemKidneys and Ureters: MRI detects tumors, cysts,...

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Updated: Aug 22, 2025

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Magnetic Resonance Imaging Assessment of Carcinogen-induced Murine Bladder Tumors

Published on: March 29, 2019

Deep learning in bladder cancer imaging: A review.

Mingyang Li¹, Zekun Jiang², Wei Shen²

¹Department of Urology, Shanghai General Hospital, Shanghai Jiao Tong University School of Medicine, Shanghai, China.

Frontiers in Oncology

|November 7, 2022

Summary

Deep learning (DL) enhances bladder cancer (BCa) imaging analysis for diagnosis and treatment. This review covers DL applications in BCa segmentation and management, highlighting current progress and future directions.

Keywords:

artificial intelligence bladder cancer computed tomography deep learning magnetic resonance imaging medical imaging

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Area of Science:

Artificial Intelligence
Medical Imaging
Oncology

Background:

Bladder cancer (BCa) is a significant global health concern.
Medical imaging is crucial for BCa diagnosis and treatment.
Deep learning (DL) shows promise in medical image analysis.

Purpose of the Study:

To review the latest advancements in applying DL to BCa imaging.
To explore DL's role in BCa segmentation, diagnosis, staging, and treatment.
To identify current limitations and future prospects of DL in BCa imaging.

Main Methods:

Review of current DL approaches for bladder segmentation.
Analysis of DL applications in BCa diagnosis and treatment management using medical images.

Main Results:

DL techniques are increasingly used for accurate bladder segmentation.
DL aids in the diagnosis, staging, and treatment planning of BCa.
Significant progress has been made in DL for BCa imaging assessment.

Conclusions:

DL offers powerful tools for improving BCa imaging analysis.
Further research is needed to address current limitations and enhance DL applications.
DL has the potential to revolutionize BCa care through advanced imaging insights.