用于骨髓增殖评估的自动三维ct / pet分割框架。

Chuong Nguyen, Joseph Havlicek, Quyen Duong, Sara Vesely, Ronald Gress, Liza Lindenberg, Peter Choyke, Jennifer Holter Chakrabarty, Kirsten Williams
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引用次数: 4

摘要

临床对骨髓的评估受限于不能全面、动态地评估骨髓空间,目前也没有自动评估骨髓空间内造血活动的方法。全面评估造血空间可用于血液疾病、恶性肿瘤、感染和药物毒性。在本文中,我们介绍了一个CT/PET三维自动框架,用于测量骨内造血室的增殖。我们首先在CT体积上使用3D图形切割进行全身骨结构分割。通过检测相邻椎骨之间的椎间盘来分割椎骨。最后,将骨髓CT体积与其对应的PET体积进行配准,获取脊髓骨髓体积。该框架在17例患者中进行了测试,在自动提取脊髓腔总量方面,平均准确率为86.37%,最差准确率为82.3%。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

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

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

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

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

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.

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