{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,4]],"date-time":"2026-09-04T11:33:51Z","timestamp":1788521631872,"version":"build-2803163510"},"reference-count":21,"publisher":"Wiley","issue":"7","license":[{"start":{"date-parts":[[2016,6,16]],"date-time":"2016-06-16T00:00:00Z","timestamp":1466035200000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0\/"},{"start":{"date-parts":[[2015,9,1]],"date-time":"2015-09-01T00:00:00Z","timestamp":1441065600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/doi.wiley.com\/10.1002\/tdm_license_1.1"}],"content-domain":{"domain":["aip.org"],"crossmark-restriction":true},"short-container-title":["Medical Physics"],"published-print":{"date-parts":[[2016,7]]},"abstract":"<jats:sec><jats:title>Purpose:<\/jats:title><jats:p>In patients with chronic obstructive pulmonary disease (COPD), diaphragm function may deteriorate due to reduced muscle fiber length. Quantitative analysis of the morphology of the diaphragm is therefore important. In the authors current study, they propose a diaphragm segmentation method for COPD patients that uses volumetric chest computed tomography (CT) data, and they provide a quantitative analysis of the diaphragmatic dimensions.<\/jats:p><\/jats:sec><jats:sec><jats:title>Methods:<\/jats:title><jats:p>Volumetric CT data were obtained from 30 COPD patients and 10 normal control patients using a 16\u2010row multidetector CT scanner (Siemens Sensation 16) with 0.75\u2010mm collimation. Diaphragm segmentation using 3D ray projections on the lower surface of the lungs was performed to identify the draft diaphragmatic lung surface, which was modeled using quadratic 3D surface fitting and robust regression in order to minimize the effects of segmentation error and parameterize diaphragm morphology. This result was visually evaluated by an expert thoracic radiologist. To take into consideration the shape features of the diaphragm, several quantification parameters\u2014including the shape index on the apex (SIA) (which was computed using gradient set to 0), principal curvatures on the apex on the fitted diaphragm surface (CA), the height between the apex and the base plane (H), the diaphragm lengths along the<jats:italic>x<\/jats:italic>\u2010,<jats:italic>y<\/jats:italic>\u2010, and<jats:italic>z<\/jats:italic>\u2010axes (XL, YL, ZL), quadratic\u2010fitted diaphragm lengths on the<jats:italic>z<\/jats:italic>\u2010axis (FZL), average curvature (C), and surface area (SA)\u2014were measured using in\u2010house software and compared with the pulmonary function test (PFT) results.<\/jats:p><\/jats:sec><jats:sec><jats:title>Results:<\/jats:title><jats:p>The overall accuracy of the combined segmentation method was 97.22% \u00b1 4.44% while the visual accuracy of the models for the segmented diaphragms was 95.28% \u00b1 2.52% (mean \u00b1 SD). The quantitative parameters, including SIA, CA, H, XL, YL, ZL, FZL, C, and SA were 0.85 \u00b1 0.05 (mm<jats:sup>\u22121<\/jats:sup>), 0.01 \u00b1 0.00 (mm<jats:sup>\u22121<\/jats:sup>), 17.93 \u00b1 10.78 (mm), 129.80 \u00b1 11.66 (mm), 163.19 \u00b1 13.45 (mm), 71.27 \u00b1 17.52 (mm), 61.59 \u00b1 16.98 (mm), 0.01 \u00b1 0.00 (mm<jats:sup>\u22121<\/jats:sup>), and 34 380.75 \u00b1 6680.06 (mm<jats:sup>2<\/jats:sup>), respectively. Several parameters were correlated with the PFT parameters.<\/jats:p><\/jats:sec><jats:sec><jats:title>Conclusions:<\/jats:title><jats:p>The authors propose an automatic method for quantitatively evaluating the morphological parameters of the diaphragm on volumetric chest CT in COPD patients. By measuring not only the conventional length and surface area but also the shape features of the diaphragm using quadratic 3D surface modeling, the proposed method is especially useful for quantifying diaphragm characteristics. Their method may be useful for assessing morphological diaphragmatic changes in COPD patients.<\/jats:p><\/jats:sec>","DOI":"10.1118\/1.4953451","type":"journal-article","created":{"date-parts":[[2016,6,16]],"date-time":"2016-06-16T18:07:29Z","timestamp":1466100449000},"page":"4273-4282","update-policy":"https:\/\/doi.org\/10.1063\/aip-crossmark-policy-page","source":"Crossref","is-referenced-by-count":8,"title":["Three\u2010dimensional quadratic modeling and quantitative evaluation of the diaphragm on a volumetric CT scan in patients with chronic obstructive pulmonary disease"],"prefix":"10.1002","volume":"43","author":[{"given":"Yongjun","family":"Chang","sequence":"first","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jangpyo","family":"Bae","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Namkug","family":"Kim","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joo\u2010Young","family":"Park","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Sang Min","family":"Lee","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joon Beom","family":"Seo","sequence":"additional","affiliation":[],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"311","published-online":{"date-parts":[[2016,6,16]]},"reference":[{"key":"e_1_2_8_2_1","doi-asserted-by":"publisher","DOI":"10.1164\/ajrccm.163.5.2101039"},{"key":"e_1_2_8_3_1","doi-asserted-by":"publisher","DOI":"10.1371\/journal.pmed.0030442"},{"key":"e_1_2_8_4_1","doi-asserted-by":"publisher","DOI":"10.1164\/ajrccm\/148.5.1351"},{"key":"e_1_2_8_5_1","doi-asserted-by":"publisher","DOI":"10.1513\/pats.200509\u2010103SF"},{"key":"e_1_2_8_6_1","doi-asserted-by":"publisher","DOI":"10.1164\/ajrccm.160.supplement_1.7"},{"key":"e_1_2_8_7_1","doi-asserted-by":"publisher","DOI":"10.1183\/09059180.00010410"},{"key":"e_1_2_8_8_1","doi-asserted-by":"publisher","DOI":"10.1183\/09059180.00010002"},{"key":"e_1_2_8_9_1","doi-asserted-by":"publisher","DOI":"10.1063\/1.365939"},{"key":"e_1_2_8_10_1","doi-asserted-by":"publisher","DOI":"10.1007\/s10278\u2010007\u20109091\u2010y"},{"key":"e_1_2_8_11_1","doi-asserted-by":"publisher","DOI":"10.1118\/1.4866836"},{"key":"e_1_2_8_12_1","first-page":"7","volume-title":"MICCAI Workshop on 3D Segmentation in the Clinic: A Grand Challenge 1","author":"Van Ginneken B.","year":"2007"},{"key":"e_1_2_8_13_1","doi-asserted-by":"publisher","DOI":"10.1145\/37402.37422"},{"key":"e_1_2_8_14_1","doi-asserted-by":"publisher","DOI":"10.1007\/s11263\u2010006\u20107934\u20105"},{"key":"e_1_2_8_15_1","doi-asserted-by":"crossref","first-page":"567","DOI":"10.1002\/9781118625590.ch25","volume-title":"Applied Regression Analysis","author":"Draper N. 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