en Medical Physics Medical Physics تحقيق بديع Original Research <div style="text-align: justify;">Background: The grading evaluation of atlas based auto-segmentation (ABAS) of organs at risk (OARs) in thorax was studied. Materials and Methods: Forty patients with thoracic cancer were included in this study, and for each thirteen thoracic OARs were delineated by an experienced radiation oncologist. The patients were randomly grouped into the training and the test dataset (20 each). The investigated ABAS strategies included single-atlas (Single), majority voting with 5 atlas matches (MV5) and simultaneous truth and performance level estimation (STAPLE) with 5 atlas matches (ST5). The Dice similarity coefficient (DSC), the difference of the Euclidean distance between centers of mass (&Delta;CMD), the difference of volume (&Delta;V), maximum Hausdorff distance (MHD) and average Hausdorff distance (AHD) between auto-segmented and manual contours were calculated. Results: Most of the index values (33/65) of ST5 were optimal. There were differences in the grading results for the five indexes. With DSC, five, four and four OARs were graded into Level 3, Level 2 and Level 1, respectively. The mean DSC values ranged from 0.88 to 0.96, from 0.73 to 0.79, and from 0.53 to 0.62 for the Level 3, Level 2 and Level 1, respectively. Conclusion: Grading evaluation of ABAS of thoracic OARs based on the DSC proved to be feasible and relatively more reliable. The thoracic OARs auto-segmentation was divided into three levels based on the DSC. Level 3 OARs can be auto-segmented, Level 2 OARs delineations need to be manually modified after the auto-segmentation, and Level 1 OARs are not recommended for the auto-segmentation.</div> Atlas based auto-segmentation, grading evaluation, thorax, organs at risk. 647 656 http://ijrr.com/browse.php?a_code=A-10-2055-49&slc_lang=en&sid=1 Y.C. Ying 7900319475328460016849 7900319475328460016849 No Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education and Center for Electronic Microscopy and Department of Physics, Wuhan University, Wuhan, China J.F. Cheng 7900319475328460016850 7900319475328460016850 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China H. Wang 7900319475328460016851 7900319475328460016851 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China H.L. Gu 7900319475328460016852 7900319475328460016852 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China H. Chen 7900319475328460016853 7900319475328460016853 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China Y. Shao 7900319475328460016854 7900319475328460016854 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China Y.H. Duan 7900319475328460016855 7900319475328460016855 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China A.H. Feng 7900319475328460016856 7900319475328460016856 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China X.L. Fu 7900319475328460016857 7900319475328460016857 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China H. Quan csp6606@sina.com 7900319475328460016858 7900319475328460016858 Yes Key Laboratory of Artificial Micro- and Nano-structures of Ministry of Education and Center for Electronic Microscopy and Department of Physics, Wuhan University, Wuhan, China Z.Y. Xu xzyong12@vip.sina.com 7900319475328460016859 7900319475328460016859 No Department of Radiation Oncology, Shanghai Chest Hospital Shanghai Jiao Tong University, Shanghai, China