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Segmentation of B-m...
Segmentation of B-mode cardiac ultrasound data by Bayesian Probability Maps
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Hansson, Mattias (författare)
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Brandt, Sami (författare)
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- Lindström, Johan (författare)
- Lund University,Lunds universitet,Matematisk statistik,Matematikcentrum,Institutioner vid LTH,Lunds Tekniska Högskola,Mathematical Statistics,Centre for Mathematical Sciences,Departments at LTH,Faculty of Engineering, LTH
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- Gudmundsson, Petri (författare)
- Malmö högskola,Institutionen för biomedicinsk vetenskap (BMV)
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- Jujic, Amra (författare)
- Lund University,Lunds universitet,Kardiovaskulär forskning - hypertoni,Forskargrupper vid Lunds universitet,Cardiovascular Research - Hypertension,Lund University Research Groups
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- Malmgren, Andreas (författare)
- Lund University,Lunds universitet,Kardiologiska klinikens forskargrupp,Forskargrupper vid Lunds universitet,Cardiology Research Group,Lund University Research Groups
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- Cheng, Yuanji (författare)
- Malmö högskola,Fakulteten för teknik och samhälle (TS)
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(creator_code:org_t)
- Elsevier, 2014
- 2014
- Engelska.
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Ingår i: Medical Image Analysis. - : Elsevier. - 1361-8415 .- 1361-8423. ; 18:7, s. 1184-1199
- Relaterad länk:
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http://www.ncbi.nlm....
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http://dx.doi.org/10...
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https://urn.kb.se/re...
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https://doi.org/10.1...
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https://lup.lub.lu.s...
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Abstract
Ämnesord
Stäng
- In this paper we present a model for describing the position distribution of the endocardium in the two-chamber apical long-axis view of the heart in clinical B-mode ultrasound cycles. We propose a novel Bayesian formulation, including priors for spatial and temporal smoothness, and preferred shapes and position. The shape model takes into account both endocardium, atrial region and apex. The likelihood is built using a statistical signal model, which attempts to closely model a censored signal. In addition, the use of a censored Gamma mixture model with unknown censoring point, to handle artefacts resulting from left-censoring of the in US clinical B-mode, is to our knowledge novel. The posterior density is sampled by the Gibbs method to estimate the expected latent variable representation of the endocardium, which we call the Bayesian Probability Map; the map describes the probability of pixels being classified as being within the endocardium. The regularization parameters of the model are estimated by cross-validation, and the results are compared against the two-chamber apical model of Chen et al.
Ämnesord
- MEDICIN OCH HÄLSOVETENSKAP -- Klinisk medicin -- Radiologi och bildbehandling (hsv//swe)
- MEDICAL AND HEALTH SCIENCES -- Clinical Medicine -- Radiology, Nuclear Medicine and Medical Imaging (hsv//eng)
Nyckelord
- Bayes
- Segmentation
- Cardiac
- B-mode ultrasound
- Censored data
Publikations- och innehållstyp
- ref (ämneskategori)
- art (ämneskategori)
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