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Related Concept Videos

Imaging Studies VII: Vascular Imaging01:19

Imaging Studies VII: Vascular Imaging

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DefinitionRenal angiography, also known as renal arteriography, is an imaging technique used to obtain a comprehensive view of blood flow and the vascular structure of blood vessels in the kidneys and surrounding areas.PurposeRenal angiography detects blood vessel abnormalities in the kidneys, such as aneurysms, stenosis, thrombosis, vascular tumors, and renal artery stenosis. It evaluates kidney function and guides interventional treatments like angioplasty or stent placement.Pre-Procedure...
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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...
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Imaging Studies IV: Magnetic Resonance Imaging01:27

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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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Automated vs. manual segmentation for small renal mass imaging.

Kristen McAlpine1, Nikhil Mirajkar2, Dominik Deniffel3,4

  • 1Division of Urology, Department of Surgery, University of Toronto, Toronto, ON, Canada.

Canadian Urological Association Journal = Journal De L'Association Des Urologues Du Canada
|February 17, 2026
PubMed
Summary
This summary is machine-generated.

Artificial intelligence (AI) significantly speeds up the segmentation of small renal masses (SRM) on CT scans compared to manual methods. AI segmentation is efficient, accurate, and acceptable, improving radiomics for SRM assessment.

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Area of Science:

  • Medical Imaging Analysis
  • Artificial Intelligence in Radiology
  • Oncology Imaging

Background:

  • Automated segmentation using AI offers rapid 3D segmentation of small renal masses (SRM).
  • Current manual segmentation methods are time-consuming.
  • AI has the potential to enhance the clinical utility of radiomics for SRM.

Purpose of the Study:

  • To compare the time, accuracy, and reliability of AI-driven versus manual segmentation of SRM on CT scans.
  • To evaluate the clinical and statistical significance of differences between segmentation methods.

Main Methods:

  • Trained an AI model (nnU-Net) on a dataset of 630 SRM CT scans, augmented with 488 from KiTS23.
  • 40 test cases were segmented by the AI, a radiologist, and a urologist.
  • Compared segmentation time and Dice coefficients; independent radiologists rated segmentation acceptability and identified segmentors.

Main Results:

  • AI segmentation was significantly faster, taking one-third the time of radiologists and one-fifth of urologists (p<0.001).
  • High inter-rater reliability was observed (median Dice 0.86-0.90).
  • AI segmentations received the highest acceptability scores (median 4.1/5), outperforming radiologists (3.8/5) and urologists (3.3/5).

Conclusions:

  • Automated AI segmentation of CT scans for SRM is efficient, accurate, and clinically acceptable.
  • This AI approach shows promise for improving radiomics applications in SRM patient care.
  • AI-driven segmentation can streamline the assessment of medical images for small renal masses.