Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms (CROSBI ID 600309)
Prilog sa skupa u zborniku | sažetak izlaganja sa skupa | međunarodna recenzija
Podaci o odgovornosti
Muštra, Mario ; Grgić, Mislav
engleski
Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms
Breast tissue segmentation into dense and fat tissue is important for determining the breast density in mammograms. Knowing the breast density is important both in diagnostic and computer-aided detection applications. There are many different ways to express the density of a breast and good quality segmentation should provide the possibility to perform accurate classification no matter which classification rule is being used. Knowing the right breast density and having the knowledge of changes in the breast density could give a hint of a process which started to happen within a patient. Mammograms generally suffer from a problem of different tissue overlapping which results in the possibility of inaccurate detection of tissue types. Fibroglandular tissue presents rather high attenuation of X-rays and is visible as brighter in the resulting image but overlapping fibrous tissue and blood vessels could easily be replaced with fibroglandular tissue in automatic segmentation algorithms. Small blood vessels and microcalcifications are also shown as bright objects with similar intensities as dense tissue but do have some properties which makes possible to suppress them from the final results. In this paper we try to divide dense and fat tissue by suppressing the scattered structures which do not represent glandular or dense tissue in order to divide mammograms more accurately in the two major tissue types. For suppressing blood vessels and microcalcifications we have used Gabor filters of different size and orientation and a combination of morphological operations on filtered image with enhanced contrast.
Gabor Filter; Breast Density; CLAHE; Morphology
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Podaci o prilogu
12-12.
2013.
objavljeno
Podaci o matičnoj publikaciji
Book of Abstracts - CCVW 2013, 2nd Croatian Computer Vision Workshop
Lončarić, Sven ; Šegvić, Siniša
Zagreb: Sveučilište u Zagrebu
Podaci o skupu
2nd Croatian Computer Vision Workshop CCVW 2013
poster
19.09.2013-19.09.2013
Zagreb, Hrvatska