TR Dizin İndeksli Yayınlar Koleksiyonu / TR Dizin Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/20.500.14365/4

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Publication Index: search.filters.publicationIndex.WoSSubject: search.filters.subject.Görüntüleme Bilimi Ve Fotoğraf Teknolojisi

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  • Article
    Citation - WoS: 19
    Citation - Scopus: 21
    Segmentation of Abdominal Organs From Mr Images Using Multi-Level Hierarchical Classification
    (Gazi Univ, Fac Engineering Architecture, 2015) Selvi, Esref; Selver, M. Alper; Kavur, Ali Emre; Guzelis, Cuneyt; Dicle, Oguz; Selver, Alper
    Medical imaging modalities can provide very detailed and informative mappings of the anatomy of a subject. These detailed and informative mappings can be processed to extract the information of interest instead of dealing with whole data (segmentation). Since manual segmentation on each slice is time consuming, tedious and operator dependent, automatic tools and techniques are needed. Segmentation of abdominal organs is a very challenging field of application due to overlapping intensity ranges of the organs, variations in human anatomy and pathology and the number of studies is very limited for Magnetic Resonance (MR), which is a relatively newer and rapidly developing imaging modality. Since it is obligatory to analyze and visualize MR images of abdominal organs (i.e. liver, right/left kidneys, spleen, pancreas, gall bladder) for several medical procedures, the main goal of this paper is to design and develop a segmentation system (method+software), which is robust to the challenges mentioned above, adaptive to the properties of the abdominal organs as well as to the interrelationships of these organs.
  • Article
    Citation - WoS: 1
    Image Quality Assessment Based on Manifold Distortion
    (Pamukkale Univ, 2021) Turkan, Mehmet
    An image quality metric is proposed by introducing a new framework for full reference image quality assessment from the perspective of image patch manifolds. Assuming that most natural scenes are sampled from low dimensional manifolds or submanifolds, perceived image degradations in structural variations can be quantitatively evaluated on the surfaces of highly nonlinear image manifolds. Manifold distortion image quality index first characterizes intrinsic geometric properties of the locally linear manifold structures of spatially local patch spaces, and then measures the deviation from the original smooth manifold structure to calculate the distortion index. Experimental results demonstrate a strong promise with a comparison to both subjective evaluation and state-of-the-art objective quality assessment methods.