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AN AUTOMATIC 3D CT/PET SEGMENTATION FRAMEWORK FOR BONE MARROW PROLIFERATION ASSESSMENT.

Chuong Nguyen1, Joseph Havlicek1, Quyen Duong2

  • 1School of Electrical and Computer Engineering, University of Oklahoma.

Proceedings. International Conference on Image Processing
|June 24, 2017
PubMed
Summary
This summary is machine-generated.

This study introduces an automated 3D framework using CT/PET scans to measure hematopoietic activity in bone marrow. This novel method accurately quanties spinal bone marrow volume, aiding in diagnosing various blood disorders.

Keywords:
CT/PET imagingbone marrow extractionbone segmentation

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Area of Science:

  • Medical imaging
  • Hematology
  • Computational anatomy

Background:

  • Current clinical bone marrow assessment lacks comprehensive and dynamic evaluation capabilities.
  • No automated methods exist for assessing hematopoietic activity within the medullary space.
  • Accurate evaluation of hematopoietic space is crucial for diagnosing blood disorders, malignancies, infections, and medication toxicity.

Purpose of the Study:

  • To introduce a novel 3D automatic framework for measuring hematopoietic compartment proliferation in osseous sites using CT/PET imaging.
  • To enable comprehensive and dynamic evaluation of the bone marrow space.
  • To facilitate improved diagnosis and monitoring of conditions affecting bone marrow.

Main Methods:

  • Full-body bone structure segmentation using 3D graph-cut on CT volumes.
  • Vertebrae segmentation through detection of intervertebral discs.
  • Registration of bone marrow CT and PET volumes to capture spinal bone marrow volume.

Main Results:

  • The automated framework successfully extracts the aggregate volume of spinal bone marrow cavities.
  • Testing on 17 patients yielded an average accuracy of 86.37% for the automated extraction.
  • The framework demonstrated a worst-case accuracy of 82.3%, indicating robust performance.

Conclusions:

  • The developed CT/PET 3D automatic framework provides an accurate and automated method for assessing spinal bone marrow volume.
  • This technology has the potential to significantly advance the clinical assessment of bone marrow and related disorders.
  • The framework offers a dynamic and comprehensive evaluation previously unavailable in clinical practice.