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Location and Orientation of the Heart01:13

Location and Orientation of the Heart

The human heart, despite its modest size and weight, is an organ of remarkable strength and endurance. Roughly the size of a fist, the heart weighs between 250 and 350 grams and is nestled within the mediastinum, the medial cavity of the thorax. It extends obliquely for about 12 to 14 cm, resting on the superior surface of the diaphragm. The heart is positioned anterior to the vertebral column and posterior to the sternum, with two-thirds of its mass lying to the left of the midsternal line.

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Related Experiment Video

Updated: May 28, 2026

3D Whole-heart Myocardial Tissue Analysis
06:53

3D Whole-heart Myocardial Tissue Analysis

Published on: April 12, 2017

Optimizing GHT-based heart localization in an automatic segmentation chain.

Axel Saalbach1, Irina Wächter-Stehle, Reinhard Kneser

  • 1Philips Research, Röntgenstrasse 24 - 26, 22335 Hamburg, Germany. axel.saalbach@philips.com

Medical Image Computing and Computer-Assisted Intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention
|October 19, 2011
PubMed
Summary

Optimizing organ localization in medical imaging, this study enhances automated segmentation accuracy and speed. By refining parameters for the Generalized Hough Transformation (GHT), researchers improved 3D heart segmentation in Computed Tomography Angiography (CTA) scans.

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Last Updated: May 28, 2026

3D Whole-heart Myocardial Tissue Analysis
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3D Whole-heart Myocardial Tissue Analysis

Published on: April 12, 2017

Automated Joint Space Detection Improves Bone Segmentation Accuracy
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Automated Joint Space Detection Improves Bone Segmentation Accuracy

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Area of Science:

  • Medical image analysis
  • Computational imaging
  • Radiology

Background:

  • Automated image analysis tools are increasingly used in clinical practice, demanding higher reliability, accuracy, and speed.
  • Systematic testing is crucial for optimizing parameter settings and algorithm design in medical image analysis.

Purpose of the Study:

  • To present an approach for optimizing organ localization within a complex segmentation chain.
  • To improve 3D heart segmentation in Computed Tomography Angiography (CTA) images using the Generalized Hough Transformation (GHT).

Main Methods:

  • Developed and tested a variant of the Generalized Hough Transformation (GHT) for organ localization.
  • Implemented a segmentation chain including organ localization, parametric organ model adaptation, and deformable adaptation.
  • Conducted systematic parameter testing on a compute cluster to evaluate GHT performance based on initialization error and computation time.

Main Results:

  • Identified optimal GHT parameters balancing reliability and speed through systematic testing.
  • Achieved improved performance using coarse image sampling, coarse Hough space resolution, and a novel filtering step to remove unspecific edges.
  • Demonstrated reduced failure rates in the overall segmentation chain due to GHT parameter optimization.

Conclusions:

  • Optimized Generalized Hough Transformation (GHT) parameters significantly enhance organ localization accuracy and speed in medical imaging.
  • The proposed systematic testing approach provides a reliable method for selecting optimal parameters in complex image analysis pipelines.
  • Refined GHT-based segmentation chains lead to improved diagnostic capabilities through reduced failure rates in 3D heart segmentation from CTA data.