Scopus İndeksli Yayınlar Koleksiyonu / Scopus Indexed Publications Collection

Permanent URI for this collectionhttps://hdl.handle.net/11147/7148

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  • Article
    A Saliency-Weighted Orthogonal Regression-Based Similarity Measure for Entropic Graphs
    (Springer, 2019) Ergün, Aslı; Ergün, Serkan; Ünlü, Mehmet Zübeyir; Güngör, Cengiz
    Various measures are used to determine similarity ratios among images before and after image registration. Image registration methods are based on finding the translation, rotation, and scaling parameters that maximize the similarity between two images by taking advantage of the feature points and densities that are found. While the similarity criterion is calculated, it is possible and advantageous to use approximation methods on the graphs based on information theory. The current study proposes a new similarity measure based on saliency-weighted orthogonal regression derived from the weighted sums of the saliency map of the orthogonal regression residuals formed on the entropic graph. It is evaluated in terms of both quantitative and qualitative methods and compared with other graph-based similarity measures.
  • Conference Object
    İskelet Dal Noktaları Kullanan Entropik Çizgelerde Çakıştırma ve Optimizasyon
    (Institute of Electrical and Electronics Engineers Inc., 2017) Ergün, Aslı; Ergün, Serkan; Ünlü, Mehmet Zübeyir; Güngör, Cengiz
    Görüntü çakıştırma işleminde görüntülerin ne kadar benzediklerinin ve iki görüntü arasındaki benzerliği maksimuma getiren kayma, dönme ve ölçeklendirme dönüşüm parametre değerlerinin bulunması gerekmektedir. Benzerlik ölçütü ve buna bağlı parametreler hesaplanırken entropik çizge diye adlandırılan, bilgi teorisi tabanlı ölçütlerin çizge üzerinde yakınsama yöntemleri kullanılabilir. Bu çalışmada, farklı entropik çizgeler üzerinde benzerlik ve optimizasyon ölçütleri karşılaştırılmış ve çizge oluşturmak için iskelet dal öznitelik noktalarının kullanılmasının başarılı sonuçlar verdiği görülmüütür.
  • Article
    Citation - WoS: 21
    Citation - Scopus: 26
    Computerized Method for Nonrigid Mr-To Breast-Image Registration
    (Elsevier Ltd., 2010) Ünlü, Mehmet Zübeyir; Krol, A.; Magri, A.; Mandel, J. A.; Lee, W.; Baum, K. G.; Lipson, E. D.; Coman, I. L.; Feiglin, D. H.
    We have developed and tested a new simple computerized finite element method (FEM) approach to MR-to-PET nonrigid breast-image registration. The method requires five-nine fiducial skin markers (FSMs) visible in MRI and PET that need to be located in the same spots on the breast and two on the flanks during both scans. Patients need to be similarly positioned prone during MRI and PET scans. This is accomplished by means of a low gamma-ray attenuation breast coil replica used as the breast support during the PET scan. We demonstrate that, under such conditions, the observed FSM displacement vectors between MR and PET images, distributed piecewise linearly over the breast volume, produce a deformed FEM mesh that reasonably approximates nonrigid deformation of the breast tissue between the MRI and PET scans. This method, which does not require a biomechanical breast tissue model, is robust and fast. Contrary to other approaches utilizing voxel intensity-based similarity measures or surface matching, our method works for matching MR with pure molecular images (i.e. PET or SPECT only). Our method does not require a good initialization and would not be trapped by local minima during registration process. All processing including FSMs detection and matching, and mesh generation can be fully automated. We tested our method on MR and PET breast images acquired for 15 subjects. The procedure yielded good quality images with an average target registration error below 4 mm (i.e. well below PET spatial resolution of 6-7 mm). Based on the results obtained for 15 subjects studied to date, we conclude that this is a very fast and a well-performing method for MR-to-PET breast-image nonrigid registration. Therefore, it is a promising approach in clinical practice. This method can be easily applied to nonrigid registration of MRI or CT of any type of soft-tissue images to their molecular counterparts such as obtained using PET and SPECT. © 2009 Elsevier Ltd. All rights reserved.