{"_buckets": {"deposit": "23de10db-02e2-439c-94df-2102cc0fe88e"}, "_deposit": {"created_by": 92, "id": "7024", "owner": "92", "owners": [92], "owners_ext": {"displayname": "", "username": ""}, "pid": {"revision_id": 0, "type": "depid", "value": "7024"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/00007024", "sets": ["user-miit"]}, "communities": ["miit"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Review of optimization Methods of Medical Image Segmentation", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Abstract Medical image segmentation is an important component in medical image analysis and diagnosis which is used as a useful application for medical image processing. Image segmentation of medical images has been implemented and studied by numerous researchers in their various research activities. Robustness\nof the method is all-time challenge in this type of application of medical image processing. The robustness has been addressed by few researchers but still remains challenging task. The performance of existing research work on medical image segmentation is improved by using optimization techniques. This paper studies and presents a critical review of existing research work that has been used for optimizing the segmentation results. An attempt has also been made to suggest a plan for further formulating a more powerful optimization method to optimize the results that could help in the automated diagnosis of different types of medical images."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Medical image segmentation"}, {"interim": "Optimization"}, {"interim": "Image diagnosis"}, {"interim": "Robustness"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2020-12-24"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Springer Proceedings.pdf", "filesize": [{"value": "171 KB"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "mimetype": "application/pdf", "size": 171000.0, "url": {"url": "https://meral.edu.mm/record/7024/files/Springer Proceedings.pdf"}, "version_id": "f754b186-31a6-4aa8-8206-ffc7f4b62274"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_journal_title": "Proceedings of the  Third International Conference on Computational Intelligence and Informatics (ICCII 2018 Dec)"}]}, "item_1583105942107": {"attribute_name": "Authors", "attribute_value_mlt": [{"subitem_authors": [{"subitem_authors_fullname": "Thuzar Khin"}, {"subitem_authors_fullname": "Kyi Kyi Khaing"}, {"subitem_authors_fullname": "Tin Mar Kyi"}]}]}, "item_1583108359239": {"attribute_name": "Upload type", "attribute_value_mlt": [{"interim": "Publication"}]}, "item_1583108428133": {"attribute_name": "Publication type", "attribute_value_mlt": [{"interim": "Journal article"}]}, "item_1583159729339": {"attribute_name": "Publication date", "attribute_value": "2019-12-15"}, "item_title": "Review of optimization Methods of Medical Image Segmentation", "item_type_id": "21", "owner": "92", "path": ["1597397014014"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000007024", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2020-12-24"}, "publish_date": "2020-12-24", "publish_status": "0", "recid": "7024", "relation": {}, "relation_version_is_last": true, "title": ["Review of optimization Methods of Medical Image Segmentation"], "weko_shared_id": -1}