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Automatic Vertebral Column Extraction by Whole-Body Bone SPECT Scan
Author(s) -
Sheng-Fang Huang,
Hao-Yu Chao,
PanFu Kao,
Wei-Chih Shen,
YuHsiang Chou,
ShuHsin Liu
Publication year - 2013
Publication title -
computational and mathematical methods in medicine
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.462
H-Index - 48
eISSN - 1748-6718
pISSN - 1748-670X
DOI - 10.1155/2013/647548
Subject(s) - vertebral column , extraction (chemistry) , column (typography) , nuclear medicine , vertebral body , spinal column , medicine , radiology , biomedical engineering , computer science , chromatography , anatomy , chemistry , surgery , telecommunications , frame (networking)
Bone extraction and division can enhance the accuracy of diagnoses based on whole-body bone SPECT data. This study developed a method for using conventional SPECT for automatic recognition of the vertebral column. A novel feature of the proposed approach is a novel “bone graph" image description method that represents the connectivity between these image regions to facilitate manipulation of morphological relationships in the skeleton before surgery. By tracking the paths shown on the bone graph, skeletal structures can be identified by performing morphological operations. The performance of the method was evaluated quantitatively and qualitatively by two experienced nuclear medicine physicians. Datasets for whole-body bone SPECT scans in 46 lung cancer patients with bone metastasis were obtained with Tc-99m MDP. The algorithm successfully segmented vertebrae in the thoracolumbar spine. The quantitative assessment shows that the segmentation method achieved an average TP, FP, and FN rates of 95.1%, 9.1%, and 4.9%. The qualitative evaluation shows an average acceptance rate of 83%, where the data for the acceptable and unacceptable groups had a Cronbach's alpha value of 0.718, which indicated reasonable internal consistency and reliability.

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