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Related Concept Videos

Magnetic Resonance Imaging01:24

Magnetic Resonance Imaging

Magnetic resonance imaging (MRI) is a noninvasive medical imaging technique based on a phenomenon of nuclear physics discovered in the 1930s, in which matter exposed to magnetic fields and radio waves was found to emit radio signals. In 1970, a physician and researcher named Raymond Damadian noticed that malignant (cancerous) tissue gave off different signals than normal body tissue. He applied for a patent for the first MRI scanning device in clinical use by the early 1980s. The early MRI...

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Related Experiment Video

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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound

Published on: March 21, 2025

Accurate prostate volume estimation using multifeature active shape models on T2-weighted MRI.

Robert Toth1, B Nicolas Bloch, Elizabeth M Genega

  • 1Department of Biomedical Engineering, Rutgers, The State University of New Jersey, Piscataway, 08854, USA.

Academic Radiology
|May 10, 2011
PubMed
Summary

A new multifeature active shape model (MFA) accurately estimates prostate volume from MRI scans. This automated method is more precise than current clinical models, requiring minimal user intervention for improved prostate cancer assessment.

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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
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Last Updated: Jun 2, 2026

A Cognitive Fusion-guided Prostate Biopsy Using Multiparametric Magnetic Resonance Imaging and Transrectal Ultrasound
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Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy
09:11

Use of MRI-ultrasound Fusion to Achieve Targeted Prostate Biopsy

Published on: April 9, 2019

Area of Science:

  • Medical imaging analysis
  • Prostate cancer diagnostics
  • Computational anatomy

Background:

  • Accurate prostate volume estimation is crucial for prostate-specific antigen density calculations and treatment response evaluation.
  • Current clinical methods using transrectal ultrasound or MRI often require manual segmentation and may lack precision.
  • Developing automated and accurate prostate volume estimation techniques is essential for improved patient management.

Purpose of the Study:

  • To present a multifeature active shape model (MFA) based segmentation scheme for automated prostate volume estimation from in vivo T2-weighted MRI.
  • To compare the accuracy of the MFA method against traditional ellipsoidal, Myschetzky, and prolate spheroid models.
  • To assess the clinical utility of MFA for precise prostate volume determination.

Main Methods:

  • Development of a multifeature active shape model (MFA) for automatic prostate boundary segmentation on T2-weighted MRI.
  • Utilizing a forward feature selection algorithm to identify optimal statistical texture descriptors for prostate boundary.
  • Deforming the MFA to accurately fit the prostate border and aggregating planimetric areas for volume calculation.
  • Comparison of MFA volume estimates against ground truth volumes derived from expert radiologist segmentation and traditional models.

Main Results:

  • The MFA method demonstrated superior accuracy in prostate volume estimation compared to clinical models.
  • Traditional models (ellipsoidal, Myschetzky, prolate spheroid) overestimated prostate volumes (volume fractions 1.14-1.96).
  • The MFA achieved a mean volume fraction of 1.05 with an r(2) value of 0.82 against ground truth, outperforming clinical models (max r(2) 0.70).

Conclusions:

  • The proposed MFA scheme offers a highly accurate and automated method for prostate volume estimation from MRI.
  • This approach requires minimal user intervention and is computationally efficient.
  • MFA provides more accurate volume estimations than current state-of-the-art clinical models, enhancing its clinical applicability.