{ "article_id": 1466, "public_id": "b7a64186-2af3-444c-be95-8b87cc28af45", "internal_identifier": null, "source_identifier": "90:15", "status": "published", "type": "research_article", "title": "Görüntü Birleştirme Yöntemleri ile Çok-modlu Medikal Görüntülerin Kaynaştırılması", "title_secondary": null, "abstract": "Çok-modlu medikal görüntü birleştirme, görüntü kalitesini artırmak için iki ya da daha fazla medikal görüntünün birleştirilmesidir. Tıbbi görüntüleme sağlık alanında teşhis, araştırma ve tedavide önemli bir rolü üstlenmektedir. Tanı ve tedavide daha doğru klinik bilgiler için farklı modlarda görüntüler kullanılır. Tıbbi görüntülemede kullanılan Tek Foton Emisyonlu Bilgisayarlı Tomografi (SPECT), Pozitron Emisyon Tomografisi (PET), Bilgisayarlı Tomografi (CT), Manyetik Rezonans Görüntüleme (MRI), gibi görüntüleme teknikleri hekimlere hastaların vücudundaki sert ve yumuşak dokular hakkında bilgi sağlarlar. Her bir görüntüleme tekniği farklı özellikleri korur ve buna bağlı olarak aynı parçanın farklı görüntüleme bilgisini elde ederler. Farklı modlardaki görüntülerin birleştirilmesindeki amaç klinik tanının doğruluğunu artırmak için daha iyi bir kontrast ve füzyon kalitesi sağlamaktır. Bu doğrultuda farklı modaliteler birleştirilir ve bu sayede lezyonların anlaşılabilirliği artırılır. İyi bir füzyon görüntüsü, kaynak görüntülerdeki yararlı bilgileri korumalı ve herhangi bir yapay olgu içermemelidir.  Bu çalışma da sekiz farklı CT ve MRI görüntü çifti üzerinde literatürde iyi bilinen klasik birleştirme yöntemleri kıyaslanmıştır. Birleştirme performansları görsel ve sayısal sonuçlara göre değerlendirilmiştir. Ayrıca buna ek olarak yöntemlerin CPU zaman tüketimleri arasında da karşılaştırma yapılmıştır. ", "language": "tr", "english_title": "Fusion of Multimodal Medical Images with Image Fusion Methods", "english_abstract": "Multimodal medical image fusion is the combination of two or more medical images to improve image quality. Medical imaging plays a vital role in diagnosis, research, and treatment in the healthcare field. Images in different modes are used for more accurate clinical information in diagnosis and treatment. Imaging techniques used in medical imaging, such as Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI), provide physicians with information about the hard and soft tissues in patients' bodies. Each imaging technique preserves different characteristics and, consequently, obtains different imaging information of the same part. The aim of combining images in different modes is to provide better contrast and fusion quality to increase the accuracy of clinical diagnosis. Accordingly, different modalities are combined, thereby increasing the intelligibility of lesions. A good fusion image should preserve useful information from the source images and should not contain any artificial phenomena. This study compares well-known classical image fusion methods on eight different pairs of CT and MRI images. Fusion performance was evaluated based on visual and numerical results. In addition, a comparison was made between the CPU time consumption of the methods.", "doi": "10.36287/setsci.6.1.0026", "doi_url": "https://doi.org/10.36287/setsci.6.1.0026", "resource_url": "https://www.set-science.com/a/b7a64186-2af3-444c-be95-8b87cc28af45", "pdf_url": "https://www.set-science.com/a/b7a64186-2af3-444c-be95-8b87cc28af45/pdf", "og_image": "https://www.set-science.com/assets/img/og-card-v2.png", "authors": [ { "public_id": "7a8ecf6d-4b9b-48ce-8847-7b36e0d7a681", "given": "Fatma", "family": "Çakıroğlu", "full": "Fatma Çakıroğlu", "literal": null, "orcid": null, "orcid_url": null, "email": "citil.fatmaa@gmail.com", "corresponding": false, "sequence": "first", "affiliations": [ { "name": "Kayseri Üniversitesi", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] }, { "public_id": "50ae9550-6b19-448d-928e-bb65e74f3efd", "given": "Rıfat", "family": "Kurban", "full": "Rıfat Kurban", "literal": null, "orcid": null, "orcid_url": null, "email": "rifat.kurban@agu.edu.tr", "corresponding": true, "sequence": "additional", "affiliations": [ { "name": "Abdullah Gül Üniversitesi", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] }, { "public_id": "316fd499-67d3-4626-9213-2daa06ba873a", "given": "Ali", "family": "Durmuş", "full": "Ali Durmuş", "literal": null, "orcid": null, "orcid_url": null, "email": "alidurmus@kayseri.edu.tr", "corresponding": false, "sequence": "additional", "affiliations": [ { "name": "Kayseri Üniversitesi", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] }, { "public_id": "8e5cdf4f-4aa6-426c-bc51-b4b97cce0868", "given": "Ercan", "family": "Karaköse", "full": "Ercan Karaköse", "literal": null, "orcid": null, "orcid_url": null, "email": "ekarakose@kayseri.edu.tr", "corresponding": false, "sequence": "additional", "affiliations": [ { "name": "Kayseri Üniversitesi", "department": null, "country": null, "country_code": null, "ror": null, "ror_url": null } ] } ], "keywords": [ "Çok modlu görüntü birleştirme", "MRI", "CT", "medikal görüntü kaynaştırma" ], "translations": [ { "language": "en", "title": "Fusion of Multimodal Medical Images with Image Fusion Methods", "abstract": "Multimodal medical image fusion is the combination of two or more medical images to improve image quality. Medical imaging plays a vital role in diagnosis, research, and treatment in the healthcare field. Images in different modes are used for more accurate clinical information in diagnosis and treatment. Imaging techniques used in medical imaging, such as Single Photon Emission Computed Tomography (SPECT), Positron Emission Tomography (PET), Computed Tomography (CT), and Magnetic Resonance Imaging (MRI), provide physicians with information about the hard and soft tissues in patients' bodies. Each imaging technique preserves different characteristics and, consequently, obtains different imaging information of the same part. The aim of combining images in different modes is to provide better contrast and fusion quality to increase the accuracy of clinical diagnosis. Accordingly, different modalities are combined, thereby increasing the intelligibility of lesions. A good fusion image should preserve useful information from the source images and should not contain any artificial phenomena. This study compares well-known classical image fusion methods on eight different pairs of CT and MRI images. Fusion performance was evaluated based on visual and numerical results. In addition, a comparison was made between the CPU time consumption of the methods.", "keywords": [ "Multimodal image fusion", "MRI", "CT", "medical image fusion." ] } ], "subjects": [], "subject_names": [], "published_date": "2023-12-29", "published_year": "2023", "received_date": null, "accepted_date": null, "volume": "15", "issue": null, "page_first": "70", "page_last": "75", "article_number": null, "conference": { "short_name": "BMYZ2023", "full_title": "Cognitive Models and Artificial Intelligence Conference", "name": "Cognitive Models and Artificial Intelligence Conference", "acronym": "BMYZ2023", "location": "Ankara, Türkiye", "start_date": "2023-10-26", "end_date": null, "public_id": "dc3a47c3-f4b3-4059-b610-f99aca33d7a0" }, "proceedings": { "title": "Cognitive Models and Artificial Intelligence Conference", "series_title": "SETSCI Conference Proceedings", "publisher": "SET Technology", "isbn": "978-605-69925-7-5", "eisbn": null, "issn": null, "eissn": "2687-5527", "doi": null, "doi_prefix": "10.36287", "slug": "setsci-volume-15-2023-legacy-90", "public_id": "33fc699d-0ab3-4057-b2e0-644dc89f900d", "url": "https://www.set-science.com/p/setsci-volume-15-2023-legacy-90" }, "license": { "name": "CC BY 4.0", "url": "https://creativecommons.org/licenses/by/4.0/", "code": "CC-BY-4.0", "open_access": true }, "copyright": { "holder": "SET Technology", "year": "2023" }, "funding_statement": null, "funders": [], "references": [ { "order": 1, "raw": "A. 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