Logo
    • English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • English 
    • English
    • Ελληνικά
    • Deutsch
    • français
    • italiano
    • español
  • Login
View Item 
  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
  •   University of Thessaly Institutional Repository
  • Επιστημονικές Δημοσιεύσεις Μελών ΠΘ (ΕΔΠΘ)
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ.
  • View Item
JavaScript is disabled for your browser. Some features of this site may not work without it.
Institutional repository
All of DSpace
  • Communities & Collections
  • By Issue Date
  • Authors
  • Titles
  • Subjects

Comparative analysis of methods for extracting vessel network on breast MRI images

Thumbnail
Author
Gaizer B.T., Vassiou K.G., Lavdas E., Arvanitis D.L., Fezoulidis I.V., Glotsos D.T.
Date
2017
Language
en
DOI
10.1088/1742-6596/931/1/012023
Keyword
Diagnosis
Extraction
Magnetic resonance imaging
Medical imaging
Cancerous lesions
Comparative analysis
Health screenings
Quantitative measurement
Vascular network
Vessel extraction
Vessel networks
Vessel structure
Image processing
Institute of Physics Publishing
Metadata display
Abstract
Digital processing of MRI images aims to provide an automatized diagnostic evaluation of regular health screenings. Cancerous lesions are proven to cause an alteration in the vessel structure of the diseased organ. Currently there are several methods used for extraction of the vessel network in order to quantify its properties. In this work MRI images (Signa HDx 3.0T, GE Healthcare, courtesy of University Hospital of Larissa) of 30 female breasts were subjected to three different vessel extraction algorithms to determine the location of their vascular network. The first method is an experiment to build a graph over known points of the vessel network; the second algorithm aims to determine the direction and diameter of vessels at these points; the third approach is a seed growing algorithm, spreading selection to neighbors of the known vessel pixels. The possibilities shown by the different methods were analyzed, and quantitative measurements were performed. The data provided by these measurements showed no clear correlation with the presence or malignancy of tumors, based on the radiological diagnosis of skilled physicians. © Published under licence by IOP Publishing Ltd.
URI
http://hdl.handle.net/11615/71895
Collections
  • Δημοσιεύσεις σε περιοδικά, συνέδρια, κεφάλαια βιβλίων κλπ. [19735]
htmlmap 

 

Browse

All of DSpaceCommunities & CollectionsBy Issue DateAuthorsTitlesSubjectsThis CollectionBy Issue DateAuthorsTitlesSubjects

My Account

LoginRegister (MyDspace)
Help Contact
DepositionAboutHelpContact Us
Choose LanguageAll of DSpace
EnglishΕλληνικά
htmlmap