Sürdürülebilir Kalkınma Amaçları
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- BildiriYalnız künye2023Shape of Masses in Contrast Mammography Images and First Order Statistical Features Classification Based on
Kobya, Mehmet Emin; Ture, Hayati; Dogan, Ramazan Ozgur; Kayikcioglu, Temel; Teymur, Aykut; Kul, Sibel
Mammography is a valuable tool in the diagnosis and staging of primary breast cancer. Contrast-enhanced mammography (CEM) combines an iodinated contrast agent with traditional mammography to increase diagnostic accuracy, especially in women with more dense parenchymal background patterns. In this study, a Decision Support System (DSS) is proposed that classifies masses using radiomic features obtained from masks of benign and malignant masses in images obtained with the CEM technique. An open-access database containing 2006 CEM images was used in this study. Radiomic features obtained from these images were used to identify differences between benign and malignant masses. The DSS uses these features to classify masses using a decision tree algorithm. This study highlights the importance of the use of iodinated contrast agents to improve diagnostic accuracy in women with more dense parenchymal background patterns. Additionally, it emphasizes the potential benefits of a DSS, in combination with radiomic features, in the diagnosis and staging of breast cancer. In conclusion, this study demonstrates that the use of radiomic features in mammography images obtained with the CEM technique is an effective way to classify benign and malignant masses.The use of this technology could be an important tool in the early diagnosis and accurate classification of breast cancer.
- MakaleAçık Erişim2015Spatial Forest Management Planning: Basic Concepts And Modeling Techniques
Kadiogullari, Ali Ihsan; Keles, Sedat; Baskent, Emin Zeki; Bingöl, Ozkan
Spatial Decision Support System is indispensable to develop spatial planning alternative by integrating spatial parameters into forest management plans using ecosystem based multiple use forest management planning concept (EBMUFM). Spatial forest planning provides several opportunities to decision makers to generate spatially implementable harvest schedules and perform spatial analyses as part of integrated planning. This paper presents the role and importance of spatial forest planning in forest management, and evaluates it in the context of Turkish forestry. Basic concepts related to spatial forest planning are explained. Some important intuitive decision support techniques (modeling techniques) widely used in spatial forest management planning were introduced. Further, spatial decision support systems for forest management planning developed in various countries were provided. Finally, it is concluded that spatial forest planning is extremely needed in EBMUFM.