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Pregled bibliografske jedinice broj: 644871

Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms


Muštra, Mario; Grgić, Mislav
Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms // Book of Abstracts - CCVW 2013, 2nd Croatian Computer Vision Workshop / Lončarić, Sven ; Šegvić, Siniša (ur.).
Zagreb: Sveučilište u Zagrebu, 2013. str. 12-12 (poster, međunarodna recenzija, sažetak, znanstveni)


CROSBI ID: 644871 Za ispravke kontaktirajte CROSBI podršku putem web obrasca

Naslov
Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms

Autori
Muštra, Mario ; Grgić, Mislav

Vrsta, podvrsta i kategorija rada
Sažeci sa skupova, sažetak, znanstveni

Izvornik
Book of Abstracts - CCVW 2013, 2nd Croatian Computer Vision Workshop / Lončarić, Sven ; Šegvić, Siniša - Zagreb : Sveučilište u Zagrebu, 2013, 12-12

Skup
2nd Croatian Computer Vision Workshop CCVW 2013

Mjesto i datum
Zagreb, Hrvatska, 19.09.2013

Vrsta sudjelovanja
Poster

Vrsta recenzije
Međunarodna recenzija

Ključne riječi
Gabor Filter; Breast Density; CLAHE; Morphology

Sažetak
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.

Izvorni jezik
Engleski

Znanstvena područja
Elektrotehnika



POVEZANOST RADA


Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb

Profili:

Avatar Url Mislav Grgić (autor)

Avatar Url Mario Muštra (autor)

Poveznice na cjeloviti tekst rada:

Pristup cjelovitom tekstu rada

Citiraj ovu publikaciju:

Muštra, Mario; Grgić, Mislav
Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms // Book of Abstracts - CCVW 2013, 2nd Croatian Computer Vision Workshop / Lončarić, Sven ; Šegvić, Siniša (ur.).
Zagreb: Sveučilište u Zagrebu, 2013. str. 12-12 (poster, međunarodna recenzija, sažetak, znanstveni)
Muštra, M. & Grgić, M. (2013) Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms. U: Lončarić, S. & Šegvić, S. (ur.)Book of Abstracts - CCVW 2013, 2nd Croatian Computer Vision Workshop.
@article{article, author = {Mu\v{s}tra, Mario and Grgi\'{c}, Mislav}, year = {2013}, pages = {12-12}, keywords = {Gabor Filter, Breast Density, CLAHE, Morphology}, title = {Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms}, keyword = {Gabor Filter, Breast Density, CLAHE, Morphology}, publisher = {Sveu\v{c}ili\v{s}te u Zagrebu}, publisherplace = {Zagreb, Hrvatska} }
@article{article, author = {Mu\v{s}tra, Mario and Grgi\'{c}, Mislav}, year = {2013}, pages = {12-12}, keywords = {Gabor Filter, Breast Density, CLAHE, Morphology}, title = {Filtering for More Accurate Dense Tissue Segmentation in Digitized Mammograms}, keyword = {Gabor Filter, Breast Density, CLAHE, Morphology}, publisher = {Sveu\v{c}ili\v{s}te u Zagrebu}, publisherplace = {Zagreb, Hrvatska} }




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