Pregled bibliografske jedinice broj: 49699
Multiresolution simulated annealing for brain image analysis
Multiresolution simulated annealing for brain image analysis // Proceedings of SPIE Vol. 3661 Medical Imaging 1999 / Hanson, Kenneth M. (ur.).
San Diego (CA), Sjedinjene Američke Države: SPIE, 1999. str. 1139-1146 (poster, međunarodna recenzija, cjeloviti rad (in extenso), znanstveni)
CROSBI ID: 49699 Za ispravke kontaktirajte CROSBI podršku putem web obrasca
Naslov
Multiresolution simulated annealing for brain image analysis
Autori
Lončarić, Sven ; Majcenić, Zoran
Vrsta, podvrsta i kategorija rada
Radovi u zbornicima skupova, cjeloviti rad (in extenso), znanstveni
Izvornik
Proceedings of SPIE Vol. 3661
Medical Imaging 1999
/ Hanson, Kenneth M. - : SPIE, 1999, 1139-1146
Skup
Medical Imaging 1999
Mjesto i datum
San Diego (CA), Sjedinjene Američke Države, 22.02.1999. - 25.02.1999
Vrsta sudjelovanja
Poster
Vrsta recenzije
Međunarodna recenzija
Ključne riječi
simulated annealing; Markov Random Field; CT; multiresolution; ICH
Sažetak
Analysis of biomedical images is an important step in quantification of
various diseases such as human spontaneous intracerebral brain hemorrhage
(ICH). In particular, the study of outcome in patients having ICH
requires measurements of various ICH parameters such as hemorrhage volume
and their change over time.
A multiresolution probabilistic approach for segmentation of CT head images
is
presented in this work. This method views the segmentation problem as
a pixel labeling problem. In this application the labels are: background,
skull, brain tissue, and ICH.
The proposed method is based on the Maximum A-Posteriori (MAP)
estimation of the unknown pixel labels.
The MAP method maximizes the a-posterior probability of segmented image
given the observed (input) image.
Markov random field (MRF) model has been used for the posterior
distribution.
The MAP estimation of the segmented image has been determined using
the simulated annealing (SA) algorithm. The SA algorithm is used to minimize
the energy function
associated with MRF posterior distribution function. A multiresolution SA
(MSA) has been developed to speed up the annealing process. MSA is presented
in detail in this work.A knowledge-based classification based on the brightness, size,
shape and relative position toward other
regions is performed at the end of the procedure. The regions are identified
as background, skull, brain, ICH and calcifications.
Izvorni jezik
Engleski
Znanstvena područja
Elektrotehnika
POVEZANOST RADA
Projekti:
036024
Ustanove:
Fakultet elektrotehnike i računarstva, Zagreb
Profili:
Sven Lončarić
(autor)