An automatic 3D CT/PET segmentation framework for bone marrow proliferation assessment

Chuong Nguyen, Joseph Havlicek, Quyen Duong, Sara Vesely, Ronald Gress, Liza Lindenberg, Peter Choyke, Jennifer Holter Chakrabarty, Kirsten Williams

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

Clinical assessment of bone marrow is limited by an inability to evaluate the marrow space comprehensively and dynamically and there is no current method for automatically assessing hematopoietic activity within the medullary space. Evaluating the hematopoietic space in its entirety could be applicable in blood disorders, malignancies, infections, and medication toxicity. In this paper, we introduce a CT/PET 3D automatic framework for measurement of the hematopoietic compartment proliferation within osseous sites. We first perform a full-body bone structure segmentation using 3D graph-cut on the CT volume. The vertebrae are segmented by detecting the discs between adjacent vertebrae. Finally, we register the bone marrow CT volume with its corresponding PET volume and capture the spinal bone marrow volume. The proposed framework was tested on 17 patients, achieving an average accuracy of 86.37% and a worst case accuracy of 82.3% in automatically extracting the aggregate volume of the spinal marrow cavities.

Original languageEnglish (US)
Title of host publication2016 IEEE International Conference on Image Processing, ICIP 2016 - Proceedings
PublisherIEEE Computer Society
Pages4126-4130
Number of pages5
ISBN (Electronic)9781467399616
DOIs
StatePublished - Aug 3 2016
Event23rd IEEE International Conference on Image Processing, ICIP 2016 - Phoenix, United States
Duration: Sep 25 2016Sep 28 2016

Publication series

NameProceedings - International Conference on Image Processing, ICIP
Volume2016-August
ISSN (Print)1522-4880

Conference

Conference23rd IEEE International Conference on Image Processing, ICIP 2016
CountryUnited States
CityPhoenix
Period9/25/169/28/16

Keywords

  • Bone marrow extraction
  • Bone segmentation
  • CT/PET imaging

ASJC Scopus subject areas

  • Software
  • Computer Vision and Pattern Recognition
  • Signal Processing

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