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Related Concept Videos

Deformation of Member under Multiple Loadings01:11

Deformation of Member under Multiple Loadings

When a rod is made of different materials or has various cross-sections, it must be divided into parts that meet the necessary conditions for determining the deformation. These parts are each characterized by their internal force, cross-sectional area, length, and modulus of elasticity. These parameters are then used to compute the deformation of the entire rod.
In the case of a member with a variable cross-section, the strain is not constant but depends on the position. The deformation of an...
Temperature Dependent Deformation01:12

Temperature Dependent Deformation

In a nonhomogeneous rod made up of steel and brass, restrained at both ends and subjected to a temperature change, several steps are involved in calculating the stress and compressive load. Due to the problem's static indeterminacy, one end support is disconnected, allowing the rod to experience the temperature change freely. Next, an unknown force is applied at the free end, triggering deformations in the rod's steel and brass portions. These deformations are then calculated and added together...
Deformations in a Transverse Cross Section01:21

Deformations in a Transverse Cross Section

When a material is subjected to uniaxial stress, it elongates or contracts in the direction of the applied force, and also undergoes changes in the perpendicular directions. This behavior is crucial for understanding how materials behave under stress and is governed by mechanical properties such as Poisson's ratio v, which measures the ratio of transverse strain to axial strain.
As the material stretches, it expands or contracts in orthogonal directions to the load. This phenomenon varies...

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Related Experiment Video

Updated: Jun 1, 2026

Automated Joint Space Detection Improves Bone Segmentation Accuracy
06:45

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Published on: November 28, 2025

Active deformation fields: dense deformation field estimation for atlas-based segmentation using the active contour

Subrahmanyam Gorthi1, Valérie Duay, Xavier Bresson

  • 1Signal Processing Laboratory (LTS5), Ecole Polytechnique Fédérale de Lausanne (EPFL), Switzerland. subrahmanyam.gorthi@epfl.ch

Medical Image Analysis
|June 8, 2011
PubMed
Summary
This summary is machine-generated.

This study introduces a novel variational framework for atlas-based segmentation, integrating active contours and optical flow. This versatile method enhances medical image analysis by enabling structure-specific registration and simulating anatomical changes.

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Three-Dimensional Shape Modeling and Analysis of Brain Structures
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Three-Dimensional Shape Modeling and Analysis of Brain Structures

Published on: November 14, 2019

Area of Science:

  • Medical Image Analysis
  • Computational Anatomy
  • Computer Vision

Background:

  • Atlas-based segmentation is crucial for medical image analysis.
  • Existing methods often lack flexibility in handling complex anatomical variations.
  • Registration accuracy is vital for reliable segmentation outcomes.

Purpose of the Study:

  • To introduce a novel variational framework for atlas-based segmentation.
  • To integrate active contour and optical flow methods for enhanced registration.
  • To demonstrate the framework's versatility across diverse medical imaging applications.

Main Methods:

  • Developed a general variational framework combining active contours and dense deformation fields from optical flow.
  • Enabled structure-of-interest-based registration for targeted segmentation.
  • Applied hierarchical registration forces for complex segmentation tasks.

Main Results:

  • Successfully simulated the growth of inconsistent structures, such as tumors, within an atlas.
  • Accurately estimated the positions of non-visible brain structures, validated against existing methods.
  • Achieved precise segmentation of lymph nodes in Head and Neck CT images.

Conclusions:

  • The proposed framework offers a versatile and general approach to atlas-based segmentation.
  • It effectively integrates multiple registration strategies for improved accuracy.
  • Demonstrated potential in simulating anatomical changes and segmenting complex structures.