@InProceedings{RittnerLotu:2008:DiTeIm,
               author = "Rittner, Leticia and Lotufo, Roberto A.",
          affiliation = "{FEEC - UNICAMP} and {FEEC - UNICAMP}",
                title = "Diffusion tensor imaging segmentation by watershed transform on 
                         tensorial morphological gradient",
            booktitle = "Proceedings...",
                 year = "2008",
               editor = "Jung, Cl{\'a}udio Rosito and Walter, Marcelo",
         organization = "Brazilian Symposium on Computer Graphics and Image Processing, 21. 
                         (SIBGRAPI)",
            publisher = "IEEE Computer Society",
              address = "Los Alamitos",
             keywords = "DTI, Image segmentation, Mathematical morphology, Watershed 
                         transform.",
             abstract = "While scalar image segmentation has been studied extensively, 
                         diffusion tensor imaging (DTI) segmentation is a relatively new 
                         and challenging task. Either existent segmentation methods have to 
                         be adapted to deal with tensorial information or completely new 
                         segmentation methods have to be developed to accomplish this task. 
                         Alternatively, what this work proposes is the computation of a 
                         tensorial morphological gradient of DTI, and its segmentation by 
                         IFT-based watershed transform. The strength of the proposed 
                         segmentation method is its simplicity and robustness, consequences 
                         of the tensorial morphological gradient computation. It enables 
                         the use, not only of well known algorithms and tools from the 
                         mathematical morphology, but also of any other segmentation method 
                         to segment DTI, since the computation of the tensorial 
                         morphological gradient transforms tensorial images in scalar ones. 
                         In order to validate the proposed method, synthetic diffusion 
                         tensor fields were generated, and Gaussian noise was added to 
                         them. A set of real DTI was also used in the method validation. 
                         All segmentation results confirmed that the proposed method is 
                         capable to segment different diffusion tensor images, including 
                         noisy and real ones.",
  conference-location = "Campo Grande, MS, Brazil",
      conference-year = "12-15 Oct. 2008",
                  doi = "10.1109/SIBGRAPI.2008.17",
                  url = "http://dx.doi.org/10.1109/SIBGRAPI.2008.17",
             language = "en",
                  ibi = "6qtX3pFwXQZG2LgkFdY/V5kVG",
                  url = "http://urlib.net/ibi/6qtX3pFwXQZG2LgkFdY/V5kVG",
           targetfile = "rittner_dtisegmentation.pdf",
        urlaccessdate = "2024, Apr. 28"
}