Hoad C L, Martel A L
Department of Medical Physics, University Hospital, Queen's Medical Centre, Nottingham, UK.
Phys Med Biol. 2002 Oct 7;47(19):3503-17. doi: 10.1088/0031-9155/47/19/305.
This paper describes a segmentation algorithm designed to separate bone from soft tissue in magnetic resonance (MR) images developed for computer-assisted surgery of the spine. The algorithm was applied to MR images of the spine of healthy volunteers. Registration experiments were carried out on a physical model of a spine generated from computed tomography (CT) data of a surgical patient. Segmented CT, manually segmented MR and MR images segmented using the developed algorithm were compared. The algorithm performed well at segmenting bone from soft tissue on images taken of healthy volunteers. Registration experiments showed similar results between the CT and MR data. The MR data, which were manually segmented, performed worse on visual verification experiments than both the CT and semi-automatic segmented data. The algorithm developed performs well at segmenting bone from soft tissue in MR images of the spine as measured using registration experiments.
本文描述了一种分割算法,该算法旨在从为脊柱计算机辅助手术而开发的磁共振(MR)图像中分离出骨骼和软组织。该算法应用于健康志愿者脊柱的MR图像。对根据手术患者的计算机断层扫描(CT)数据生成的脊柱物理模型进行了配准实验。比较了分割后的CT、手动分割的MR以及使用所开发算法分割的MR图像。该算法在分割健康志愿者图像中的骨骼和软组织方面表现良好。配准实验表明CT和MR数据之间的结果相似。在视觉验证实验中,手动分割的MR数据的表现比CT和半自动分割的数据都要差。使用配准实验进行测量时,所开发的算法在分割脊柱MR图像中的骨骼和软组织方面表现良好。