{"_buckets": {"deposit": "3284cae3-3bb1-4977-b7f4-6d5e12aa98fa"}, "_deposit": {"created_by": 14, "id": "2019516", "owner": "14", "owners": [14], "owners_ext": {"displayname": "kugai", "username": null}, "pid": {"revision_id": 0, "type": "depid", "value": "2019516"}, "status": "published"}, "_oai": {"id": "oai:u-ryukyu.repo.nii.ac.jp:02019516", "sets": ["1642838159351", "1642838409905"]}, "author_link": [], "item_1617186331708": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Automatic bronchial segmentation on ultra-HRCT scans: advantage of the 1024-matrix size with 0.25-mm slice thickness reconstruction", "subitem_1551255648112": "en"}, {"subitem_1551255647225": "\u8d85\u9ad8\u7cbe\u7d30CT\u306b\u304a\u3051\u308b\u6c17\u7ba1\u652f\u81ea\u52d5\u62bd\u51fa\u80fd\u306e\u691c\u8a0e\uff1a 1024\u30de\u30c8\u30ea\u30af\u30b9\u30680.25mm \u30b9\u30e9\u30a4\u30b9\u539a\u3092\u7528\u3044\u305f\u753b\u50cf\u5316\u306b\u3088\u308b\u9032\u6b69", "subitem_1551255648112": "ja"}]}, "item_1617186419668": {"attribute_name": "Creator", "attribute_type": "creator", "attribute_value_mlt": [{"creatorNames": [{"creatorName": "\u4e2d\u5c71, \u6709\u9999", "creatorNameLang": "ja"}]}]}, "item_1617186476635": {"attribute_name": "Access Rights", "attribute_value_mlt": [{"subitem_1522299639480": "open access", "subitem_1600958577026": "http://purl.org/coar/access_right/c_abf2"}]}, "item_1617186609386": {"attribute_name": "Subject", "attribute_value_mlt": [{"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Ultra-high-resolution computed tomograph"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Bronchu"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Airway segmentatio"}, {"subitem_1522299896455": "en", "subitem_1522300014469": "Other", "subitem_1523261968819": "Quantitative measurement"}]}, "item_1617186626617": {"attribute_name": "Description", "attribute_value_mlt": [{"subitem_description": "Purpose The aim of this study was to evaluate the advantages of ultra-high-resolution computed tomography (U-HRCT)\nfor automatic bronchial segmentation.Materials and methods This retrospective study was approved by the Institutional Review Board, and written informed consent\nwas waived. Thirty-three consecutive patients who underwent chest CT by a U-HRCT scanner were enrolled. In each\npatient, CT data were reconstructed by two different protocols: 512 x 512 matrix with 0.5-mm slice thickness (conventional\nHRCT mode) and 1024x 1024 matrix with 0.25-mm slice thickness (U-HRCT mode). We used a research workstation to\ncompare the two CT modes with regard to the numbers and total lengths of the automatically segmented bronchi.Results Significantly greater numbers and longer lengths of peripheral bronchi were segmented in the U-HRCT mode than\nin the conventional HRCT mode (P \u003c 0.001, for fifth-to eighth-generation bronchi). For example, the mean numbers and\ntotal lengths of the sixth-generation bronchi were 81 and 1048 mm in the U-HRCT mode and 59 and 538 mm in the conventional\nHRCT mode.Conclusions The U-HRCT mode greatly improves automatic airway segmentation for the more peripheral bronchi, compared\nwith the conventional HRCT mode. This advantage can be applied to routine clinical care, such as virtual bronchoscopy and\nautomatic lung segmentation.", "subitem_description_language": "en", "subitem_description_type": "Abstract"}]}, "item_1617186643794": {"attribute_name": "Publisher", "attribute_value_mlt": [{"subitem_1522300295150": "ja", "subitem_1522300316516": "\u7409\u7403\u5927\u5b66"}]}, "item_1617186702042": {"attribute_name": "Language", "attribute_value_mlt": [{"subitem_1551255818386": "eng"}]}, "item_1617187087799": {"attribute_name": "Dissertation Number", "attribute_value_mlt": [{"subitem_1551256171004": "\u7532\u7b2c522\u53f7"}]}, "item_1617187112279": {"attribute_name": "Degree Name", "attribute_value_mlt": [{"subitem_1551256126428": "\u535a\u58eb(\u533b\u5b66)", "subitem_1551256129013": "ja"}]}, "item_1617187136212": {"attribute_name": "Date Granted", "attribute_value_mlt": [{"subitem_1551256096004": "2022-03-23"}]}, "item_1617258105262": {"attribute_name": "Resource Type", "attribute_value_mlt": [{"resourcetype": "doctoral thesis", "resourceuri": "http://purl.org/coar/resource_type/c_db06"}]}, "item_1617265215918": {"attribute_name": "Version Type", "attribute_value_mlt": [{"subitem_1522305645492": "VoR", "subitem_1600292170262": "http://purl.org/coar/version/c_970fb48d4fbd8a85"}]}, "item_1617605131499": {"attribute_name": "File", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2022-10-06"}], "download_preview_message": "", "file_order": 0, "filename": "iken522abstract.pdf", "filesize": [{"value": "906 KB"}], "future_date_message": "", "is_thumbnail": false, "mimetype": "", "size": 906000.0, "url": {"objectType": "abstract", "url": "https://u-ryukyu.repo.nii.ac.jp/record/2019516/files/iken522abstract.pdf"}, "version_id": "5e510b84-ff2f-4921-8b54-7828b3d3392a"}, {"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2022-10-06"}], "download_preview_message": "", "file_order": 1, "filename": "iken522review.pdf", "filesize": [{"value": "1 MB"}], "future_date_message": "", "is_thumbnail": false, "mimetype": "", "size": 1000000.0, "url": {"objectType": "other", "url": "https://u-ryukyu.repo.nii.ac.jp/record/2019516/files/iken522review.pdf"}, "version_id": "4a0c3029-a54b-4ebc-a0d1-2ba99ecaa8d6"}]}, "item_1617944105607": {"attribute_name": "Degree Grantor", "attribute_value_mlt": [{"subitem_1551256015892": [{"subitem_1551256027296": "18001", "subitem_1551256029891": "kakenhi"}], "subitem_1551256037922": [{"subitem_1551256042287": "\u7409\u7403\u5927\u5b66", "subitem_1551256047619": "ja"}]}]}, "item_title": "Automatic bronchial segmentation on ultra-HRCT scans: advantage of the 1024-matrix size with 0.25-mm slice thickness reconstruction", "item_type_id": "59", "owner": "14", "path": ["1642838159351", "1642838409905"], "permalink_uri": "http://hdl.handle.net/20.500.12000/0002019516", "pubdate": {"attribute_name": "PubDate", "attribute_value": "2022-08-31"}, "publish_date": "2022-08-31", "publish_status": "0", "recid": "2019516", "relation": {}, "relation_version_is_last": true, "title": ["Automatic bronchial segmentation on ultra-HRCT scans: advantage of the 1024-matrix size with 0.25-mm slice thickness reconstruction"], "weko_shared_id": -1}