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

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.

DOI: 10.1109/ICIP.2016.7533136

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Cite this paper

@article{Nguyen2016AnA3, title={An automatic 3D CT/PET segmentation framework for bone marrow proliferation assessment}, author={Chuong T. Nguyen and Joseph P. Havlicek and Quyen Duong and Sara K. Vesely and Ronald E Gress and Liza Lindenberg and Peter L. Choyke and Jennifer Holter Chakrabarty and Kirsten M Williams}, journal={2016 IEEE International Conference on Image Processing (ICIP)}, year={2016}, pages={4126-4130} }