Information

Abstract

Breast cancer is the second leading cause of cancer deaths in women today. Although X-ray mammography is regarded as the most widely used method for early detection of breast cancer, the use of Contrast Enhanced MRI (CE-MRI) has gained considerable attention in the past years. Especially, Dynamic CE-MRI (DCE-MRI) considerably improves tumor classification by analyzing the flow of contrast agent within the breast tissue. In this paper we present MammoExplorer, an advanced CAD application that combines advanced interaction, segmentation and visualization techniques to explore Breast DCE-MRI data. In addition, we present a novel graphical representation of DCE-MRI data, new segmentation approaches, and a new way to explore temporal data.

Additional Files and Images

Additional images and videos

Additional files

Weblinks

No further information available.

BibTeX

@techreport{TR-186-2-05-02,
  title =      "MammoExplorer: An Advanced CAD Application for Breast
               DCE-MRI",
  author =     "Ernesto Coto and S\"{o}ren Grimm and Stefan Bruckner and
               Eduard Gr\"{o}ller and Armin Kanitsar and Omaira Rodriguez",
  year =       "2005",
  abstract =   "Breast cancer is the second leading cause of cancer deaths
               in women today. Although X-ray mammography is regarded as
               the most widely used method for early detection of breast
               cancer, the use of Contrast Enhanced MRI (CE-MRI) has gained
               considerable attention in the past years. Especially,
               Dynamic CE-MRI (DCE-MRI) considerably improves tumor
               classification by analyzing the flow of contrast agent
               within the breast tissue. In this paper we present
               MammoExplorer, an advanced CAD application that combines
               advanced interaction, segmentation and visualization
               techniques to explore Breast DCE-MRI data. In addition, we
               present a novel graphical representation of DCE-MRI data,
               new segmentation approaches, and a new way to explore
               temporal data.",
  month =      apr,
  number =     "TR-186-2-05-02",
  address =    "Favoritenstrasse 9-11/E193-02, A-1040 Vienna, Austria",
  institution = "Institute of Computer Graphics and Algorithms, Vienna
               University of Technology ",
  note =       "human contact: technical-report@cg.tuwien.ac.at",
  keywords =   "Contrast Enhanced MRI, CAD, Breast cancer",
  URL =        "https://www.cg.tuwien.ac.at/research/publications/2005/TR-186-2-05-02/",
}