Nguyen Chuong, Havlicek Joseph, Duong Quyen, Vesely Sara, Gress Ronald, Lindenberg Liza, Choyke Peter, Chakrabarty Jennifer Holter, Williams Kirsten
School of Electrical and Computer Engineering, University of Oklahoma.
Dept. of Biostatistics and Epidemiology, University of Oklahoma Health Sciences Center.
Proc Int Conf Image Proc. 2016 Sep;2016:4126-4130. doi: 10.1109/ICIP.2016.7533136. Epub 2016 Aug 19.
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.
骨髓的临床评估受到无法全面、动态评估骨髓腔的限制，目前也没有自动评估骨髓腔内造血活性的方法。对整个造血空间进行评估可能适用于血液疾病、恶性肿瘤、感染和药物毒性。在本文中，我们介绍了一种用于测量骨部位造血区增殖的CT/PET 3D自动框架。我们首先在CT体积上使用3D图割进行全身骨骼结构分割。通过检测相邻椎体之间的椎间盘来分割椎体。最后，我们将骨髓CT体积与其相应的PET体积配准，并获取脊柱骨髓体积。该提议的框架在17名患者身上进行了测试，在自动提取脊髓腔总体积方面，平均准确率达到86.37%，最坏情况下的准确率为82.3%。
