{"created":"2023-06-19T11:41:15.021059+00:00","id":9940,"links":{},"metadata":{"_buckets":{"deposit":"35943a8b-d4d3-4c31-acb9-c86e26fd2c91"},"_deposit":{"created_by":16,"id":"9940","owners":[16],"pid":{"revision_id":0,"type":"depid","value":"9940"},"status":"published"},"_oai":{"id":"oai:mie-u.repo.nii.ac.jp:00009940","sets":["366:640:660:667"]},"author_link":[],"item_7_biblio_info_6":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicIssueDates":{"bibliographicIssueDate":"2012-01-01","bibliographicIssueDateType":"Issued"}}]},"item_7_contributor_61":{"attribute_name":"修士論文指導教員","attribute_value_mlt":[{"contributorNames":[{"contributorName":"小林, 英雄","lang":"ja"}]}]},"item_7_description_14":{"attribute_name":"フォーマット","attribute_value_mlt":[{"subitem_description":"application/pdf","subitem_description_type":"Other"}]},"item_7_description_4":{"attribute_name":"抄録","attribute_value_mlt":[{"subitem_description":"Optical Coherence Tomography (OCT) is an emerging technology that can provide high-resolution cross-sectional images of the retina for identifying, and quantitatively assessing of the retinal disease. On OCT images, retinal disease area appears in two conditions, either white or black color. Quantitative information of retina is needed to evaluate the degree of disease and the effectiveness of the treatment. In the previous researches, we already proposed some automatic measurement methods of the thickness between Inner Limiting Membrane (ILM) and Retinal Pigment Epithelium (RPE) from OCT images. One of the methods used was the combination of bottom-up image processing technique and a proposed contour active net model (One Directional Active Net (ODAN)), but resulted in similar problems namely inability to extract abnormal area in some cases and inability to extract the abnormal area in white condition. The main objective of this research is to develop a new generation computer aided diagnosis support system for OCT. The experimental materials used in this research, consists of two sets of 128 pieces of two-dimensional images of a retina. One set was obtained from a drusen patient and another set from a diabetic macular ederma (DME) patient. All of these images were digitalized to a pixel size of 6μm × 6μm, 16-bit gray scale with resolution 512 × 480 pixels. Out of 128 pieces of OCT images from each set, only 36 pieces of images which contained abnormal area were used as the final experimental materials. In this research, we used two conventional methods and proposed three new methods. At the end of the experiment, a comparison was made xiv between different methods of extracting the abnormal area from selected images. The results showed that a new proposed method which is border tracking procedure using regional statistics method provides the best extraction rate compared to others. We hope that this procedure may be added in the commercial OCT unit to evaluate the degree of retinal disease suffered and enable appropriate response for treatment.","subitem_description_language":"en","subitem_description_type":"Abstract"}]},"item_7_description_5":{"attribute_name":"内容記述","attribute_value_mlt":[{"subitem_description":"三重大学大学院工学研究科博士後期課程システム工学専攻","subitem_description_type":"Other"},{"subitem_description":"77p","subitem_description_type":"Other"}]},"item_7_publisher_30":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"三重大学"}]},"item_7_text_65":{"attribute_name":"資源タイプ（三重大）","attribute_value_mlt":[{"subitem_text_value":"Doctoral Dissertation / 博士論文"}]},"item_7_version_type_15":{"attribute_name":"著者版フラグ","attribute_value_mlt":[{"subitem_version_resource":"http://purl.org/coar/version/c_970fb48d4fbd8a85","subitem_version_type":"VoR"}]},"item_creator":{"attribute_name":"著者","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Mohd, Fadzil Bin Abdul Kadir","creatorNameLang":"en"}]}]},"item_files":{"attribute_name":"ファイル情報","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_date","date":[{"dateType":"Available","dateValue":"2017-02-20"}],"displaytype":"detail","filename":"2012D001.pdf","filesize":[{"value":"2.6 MB"}],"format":"application/pdf","mimetype":"application/pdf","url":{"label":"2012D001.pdf","url":"https://mie-u.repo.nii.ac.jp/record/9940/files/2012D001.pdf"},"version_id":"5c0340e0-1157-4dbf-ab3b-3580bbd53159"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourcetype":"thesis","resourceuri":"http://purl.org/coar/resource_type/c_46ec"}]},"item_title":"Automatic Extraction of Retinal Disease Area for Optical Coherence Tomography Image","item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"Automatic Extraction of Retinal Disease Area for Optical Coherence Tomography Image","subitem_title_language":"en"}]},"item_type_id":"7","owner":"16","path":["667"],"pubdate":{"attribute_name":"PubDate","attribute_value":"2013-11-25"},"publish_date":"2013-11-25","publish_status":"0","recid":"9940","relation_version_is_last":true,"title":["Automatic Extraction of Retinal Disease Area for Optical Coherence Tomography Image"],"weko_creator_id":"16","weko_shared_id":-1},"updated":"2023-11-20T02:38:33.712517+00:00"}