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Related Experiment Video

Updated: Apr 21, 2026

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

An In Vitro 3D Model and Computational Pipeline to Quantify the Vasculogenic Potential of iPSC-Derived Endothelial Progenitors

Published on: May 13, 2019

Three-dimensional vessel segmentation using a novel combinatory filter framework.

Y Ding¹, W O C Ward, T Wästerlid

¹School of Computer Science, University of Nottingham, Nottingham NG8 1BB, UK.

Physics in Medicine and Biology

|October 29, 2014

Summary

This summary is machine-generated.

This study introduces a new 3D blood vessel segmentation method, improving accuracy for microvessels in noisy medical images. The novel approach enhances diagnostic reliability by combining line and Hessian filters.

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From Voxels to Knowledge: A Practical Guide to the Segmentation of Complex Electron Microscopy 3D-Data

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Published on: August 13, 2014

Area of Science:

Medical Imaging
Image Analysis
Biomedical Engineering

Background:

Blood vessel segmentation is crucial for medical diagnostics.
Existing Hessian-based methods struggle with high-density microvessels and noise.
Segmentation errors include missing, broken, or merged vessels, impacting diagnostic accuracy.

Purpose of the Study:

To present a novel 3D blood vessel segmentation method.
To improve segmentation of microvessels in noisy and inhomogeneous medical images.
To enable scale-based vessel separation for diverse medical applications.

Main Methods:

A novel method combining line filters and Hessian-based vessel filters for 3D segmentation.
The method is designed to be robust against background noise and image inhomogeneity.
Vessels are separated based on scale/thickness.

Main Results:

The proposed method demonstrates reliability in segmenting noisy and inhomogeneous images.
Successfully segments high-density microvessels, overcoming limitations of traditional methods.
Enables scale-based separation of vessels.

Conclusions:

The novel method offers improved 3D blood vessel segmentation, particularly for microvessels.
It provides a reliable solution for noisy and inhomogeneous medical images.
The technique supports quantitative vessel analysis using multifractal analysis, revealing fractal properties.