{"id":101634,"updated":"2025-01-21T11:07:56.557268+00:00","links":{},"created":"2025-01-18T23:47:09.560792+00:00","metadata":{"_oai":{"id":"oai:ipsj.ixsq.nii.ac.jp:00101634","sets":["934:1162:7602"]},"path":["7602"],"owner":"11","recid":"101634","title":["An Extended Method of Higher-order Local Autocorrelation Feature Extraction for Classification of Histopathological Images"],"pubdate":{"attribute_name":"公開日","attribute_value":"2011-12-28"},"_buckets":{"deposit":"acebdba0-6409-419e-a548-9ce723845af5"},"_deposit":{"id":"101634","pid":{"type":"depid","value":"101634","revision_id":0},"owners":[11],"status":"published","created_by":11},"item_title":"An Extended Method of Higher-order Local Autocorrelation Feature Extraction for Classification of Histopathological Images","author_link":["0","0"],"item_titles":{"attribute_name":"タイトル","attribute_value_mlt":[{"subitem_title":"An Extended Method of Higher-order Local Autocorrelation Feature Extraction for Classification of Histopathological Images"},{"subitem_title":"An Extended Method of Higher-order Local Autocorrelation Feature Extraction for Classification of Histopathological Images","subitem_title_language":"en"}]},"item_keyword":{"attribute_name":"キーワード","attribute_value_mlt":[{"subitem_subject":"Special Issue on MIRU2010 - Research Paper","subitem_subject_scheme":"Other"}]},"item_type_id":"3","publish_date":"2011-12-28","item_3_text_3":{"attribute_name":"著者所属","attribute_value_mlt":[{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"Department of Information Science, Toho University／Presently with NEC Soft Ltd."},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"Department of Information Science, Toho University"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)"},{"subitem_text_value":"Department of Surgical Pathology, Toho University Sakura Medical Center"},{"subitem_text_value":"Department of Surgical Pathology, Toho University Sakura Medical Center"}]},"item_3_text_4":{"attribute_name":"著者所属(英)","attribute_value_mlt":[{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Science, Toho University／Presently with NEC Soft Ltd.","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"Department of Information Science, Toho University","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"National Institute of Advanced Industrial Science and Technology (AIST)","subitem_text_language":"en"},{"subitem_text_value":"Department of Surgical Pathology, Toho University Sakura Medical Center","subitem_text_language":"en"},{"subitem_text_value":"Department of Surgical Pathology, Toho University Sakura Medical Center","subitem_text_language":"en"}]},"item_language":{"attribute_name":"言語","attribute_value_mlt":[{"subitem_language":"eng"}]},"item_publisher":{"attribute_name":"出版者","attribute_value_mlt":[{"subitem_publisher":"情報処理学会","subitem_publisher_language":"ja"}]},"publish_status":"0","weko_shared_id":-1,"item_file_price":{"attribute_name":"Billing file","attribute_type":"file","attribute_value_mlt":[{"url":{"url":"https://ipsj.ixsq.nii.ac.jp/record/101634/files/IPSJ-TCVA0300024.pdf"},"date":[{"dateType":"Available","dateValue":"2013-12-28"}],"format":"application/pdf","billing":["billing_file"],"filename":"IPSJ-TCVA0300024.pdf","filesize":[{"value":"3.1 MB"}],"mimetype":"application/pdf","priceinfo":[{"tax":["include_tax"],"price":"0","billingrole":"5"},{"tax":["include_tax"],"price":"0","billingrole":"6"},{"tax":["include_tax"],"price":"0","billingrole":"20"},{"tax":["include_tax"],"price":"0","billingrole":"44"}],"accessrole":"open_date","version_id":"14e2a423-ff4f-4a0e-aa25-fed210a07862","displaytype":"detail","licensetype":"license_note","license_note":"Copyright (c) 2011 by the Information Processing Society of Japan"}]},"item_3_creator_5":{"attribute_name":"著者名","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hirokazu, Nosato"},{"creatorName":"Tsukasa, Kurihara"},{"creatorName":"Hidenori, Sakanashi"},{"creatorName":"Masahiro, Murakawa"},{"creatorName":"Takumi, Kobayashi"},{"creatorName":"Tatsumi, Furuya"},{"creatorName":"Tetsuya, Higuchi"},{"creatorName":"Nobuyuki, Otsu"},{"creatorName":"Kensuke, Terai"},{"creatorName":"Nobuyuki, Hiruta"}],"nameIdentifiers":[{}]}]},"item_3_creator_6":{"attribute_name":"著者名(英)","attribute_type":"creator","attribute_value_mlt":[{"creatorNames":[{"creatorName":"Hirokazu, Nosato","creatorNameLang":"en"},{"creatorName":"Tsukasa, Kurihara","creatorNameLang":"en"},{"creatorName":"Hidenori, Sakanashi","creatorNameLang":"en"},{"creatorName":"Masahiro, Murakawa","creatorNameLang":"en"},{"creatorName":"Takumi, Kobayashi","creatorNameLang":"en"},{"creatorName":"Tatsumi, Furuya","creatorNameLang":"en"},{"creatorName":"Tetsuya, Higuchi","creatorNameLang":"en"},{"creatorName":"Nobuyuki, Otsu","creatorNameLang":"en"},{"creatorName":"Kensuke, Terai","creatorNameLang":"en"},{"creatorName":"Nobuyuki, Hiruta","creatorNameLang":"en"}],"nameIdentifiers":[{}]}]},"item_3_source_id_9":{"attribute_name":"書誌レコードID","attribute_value_mlt":[{"subitem_source_identifier":"AA12394973 ","subitem_source_identifier_type":"NCID"}]},"item_resource_type":{"attribute_name":"資源タイプ","attribute_value_mlt":[{"resourceuri":"http://purl.org/coar/resource_type/c_6501","resourcetype":"journal article"}]},"item_3_source_id_11":{"attribute_name":"ISSN","attribute_value_mlt":[{"subitem_source_identifier":"1882-6695","subitem_source_identifier_type":"ISSN"}]},"item_3_description_7":{"attribute_name":"論文抄録","attribute_value_mlt":[{"subitem_description":"In histopathological diagnosis, a clinical pathologist discriminates between normal tissues and cancerous tissues. However, recently, the shortage of clinical pathologists is posing increasing burdens on meeting the demands for such diagnoses, and this is becoming a serious social problem. Currently, it is necessary to develop new medical technologies to help reduce their burdens. Therefore, as a diagnostic support technology, this paper describes an extended method of HLAC feature extraction for classification of histopathological images into normal and anomaly. The proposed method can automatically classify cancerous images as anomaly by using an extended geometric invariant HLAC features with rotation- and reflection-invariant properties from three-level histopathological images, which are segmented into nucleus, cytoplasm and background. In conducted experiments, we demonstrate a reduction in the rate of not only false-negative errors but also of false-positive errors, where a normal image is falsely classified as an image with an anomaly that is suspected as being cancerous.","subitem_description_type":"Other"}]},"item_3_description_8":{"attribute_name":"論文抄録(英)","attribute_value_mlt":[{"subitem_description":"In histopathological diagnosis, a clinical pathologist discriminates between normal tissues and cancerous tissues. However, recently, the shortage of clinical pathologists is posing increasing burdens on meeting the demands for such diagnoses, and this is becoming a serious social problem. Currently, it is necessary to develop new medical technologies to help reduce their burdens. Therefore, as a diagnostic support technology, this paper describes an extended method of HLAC feature extraction for classification of histopathological images into normal and anomaly. The proposed method can automatically classify cancerous images as anomaly by using an extended geometric invariant HLAC features with rotation- and reflection-invariant properties from three-level histopathological images, which are segmented into nucleus, cytoplasm and background. In conducted experiments, we demonstrate a reduction in the rate of not only false-negative errors but also of false-positive errors, where a normal image is falsely classified as an image with an anomaly that is suspected as being cancerous.","subitem_description_type":"Other"}]},"item_3_biblio_info_10":{"attribute_name":"書誌情報","attribute_value_mlt":[{"bibliographicPageEnd":"221","bibliographic_titles":[{"bibliographic_title":"IPSJ Transactions on Computer Vision and Applications（CVA）"}],"bibliographicPageStart":"211","bibliographicIssueDates":{"bibliographicIssueDate":"2011-12-28","bibliographicIssueDateType":"Issued"},"bibliographicVolumeNumber":"3"}]},"relation_version_is_last":true,"weko_creator_id":"11"}}