A variational framework for integrating segmentation and registration through active contours.


:Traditionally, segmentation and registration have been solved as two independent problems, even though it is often the case that the solution to one impacts the solution to the other. In this paper, we introduce a geometric, variational framework that uses active contours to simultaneously segment and register features from multiple images. The key observation is that multiple images may be segmented by evolving a single contour as well as the mappings of that contour into each image.


Med Image Anal


Medical image analysis


Yezzi A,Zöllei L,Kapur T




Has Abstract


2003-06-01 00:00:00














  • Unmixing dynamic PET images with variable specific binding kinetics.

    abstract::To analyze dynamic positron emission tomography (PET) images, various generic multivariate data analysis techniques have been considered in the literature, such as principal component analysis (PCA), independent component analysis (ICA), factor analysis and nonnegative matrix factorization (NMF). Nevertheless, these c...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Cavalcanti YC,Oberlin T,Dobigeon N,Stute S,Ribeiro M,Tauber C

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  • Pseudo-healthy synthesis with pathology disentanglement and adversarial learning.

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    journal_title:Medical image analysis

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    authors: Xia T,Chartsias A,Tsaftaris SA

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  • Quantification of the detailed cardiac left ventricular trabecular morphogenesis in the mouse embryo.

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    journal_title:Medical image analysis

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    authors: Paun B,Bijnens B,Cook AC,Mohun TJ,Butakoff C

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Lee S,Reinhardt JM,Cattin PC,Abràmoff MD

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Zhang X,Thibault G,Decencière E,Marcotegui B,Laÿ B,Danno R,Cazuguel G,Quellec G,Lamard M,Massin P,Chabouis A,Victor Z,Erginay A

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    journal_title:Medical image analysis

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    authors: Rivaz H,Karimaghaloo Z,Collins DL

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    pub_type: 杂志文章


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    journal_title:Medical image analysis

    pub_type: 杂志文章


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    journal_title:Medical image analysis

    pub_type: 杂志文章


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    journal_title:Medical image analysis

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    pub_type: 杂志文章


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    journal_title:Medical image analysis

    pub_type: 杂志文章


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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Zhang M,Fletcher PT

    更新日期:2015-10-01 00:00:00

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Barnhill E,Hollis L,Sack I,Braun J,Hoskins PR,Pankaj P,Brown C,van Beek EJR,Roberts N

    更新日期:2017-01-01 00:00:00

  • Involuntary eye motion correction in retinal optical coherence tomography: Hardware or software solution?

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    journal_title:Medical image analysis

    pub_type: 杂志文章,评审


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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Weldeselassie YT,Barmpoutis A,Atkins MS

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  • Computer technology in detection and staging of prostate carcinoma: a review.

    abstract::After two decades of increasing interest and research activity, computer-assisted diagnostic approaches are reaching the stage where more routine deployment in clinical practice is becoming a possibility [Kruppinski, E.A., 2004. Computer-aided detection in clinical environment: Benefits and challenges for radiologists...

    journal_title:Medical image analysis

    pub_type: 杂志文章,评审


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    abstract::Although white matter hyperintensities evolve in the course of ageing, few solutions exist to consider the lesion segmentation problem longitudinally. Based on an existing automatic lesion segmentation algorithm, a longitudinal extension is proposed. For evaluation purposes, a longitudinal lesion simulator is created ...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Sudre CH,Cardoso MJ,Ourselin S,Alzheimer’s Disease Neuroimaging Initiative.

    更新日期:2017-05-01 00:00:00

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Huang Q,Xian Y,Yang D,Qu H,Yi J,Wu P,Metaxas DN

    更新日期:2021-02-01 00:00:00

  • Luminosity and contrast normalization in retinal images.

    abstract::Retinal images are routinely acquired and assessed to provide diagnostic evidence for many important diseases, e.g. diabetes or hypertension. Because of the acquisition process, very often these images are non-uniformly illuminated and exhibit local luminosity and contrast variability. This problem may seriously affec...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Foracchia M,Grisan E,Ruggeri A

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    abstract::Automated delineation of anatomical structures in chest radiographs is difficult due to superimposition of multiple structures. In this work an automated technique to segment the clavicles in posterior-anterior chest radiographs is presented in which three methods are combined. Pixel classification is applied in two s...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Hogeweg L,Sánchez CI,de Jong PA,Maduskar P,van Ginneken B

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  • An automated pipeline for cortical sulcal fundi extraction.

    abstract::In this paper, we propose a novel automated pipeline for extraction of sulcal fundi from triangulated cortical surfaces. This method consists of four consecutive steps. Firstly, we adopt a finite difference method to estimate principal curvatures, principal directions and curvature derivatives, along the principal dir...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Li G,Guo L,Nie J,Liu T

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Xia Y,Zhang L,Ravikumar N,Attar R,Piechnik SK,Neubauer S,Petersen SE,Frangi AF

    更新日期:2021-01-01 00:00:00

  • Cardiac function estimation from MRI using a heart model and data assimilation: advances and difficulties.

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    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Sermesant M,Moireau P,Camara O,Sainte-Marie J,Andriantsimiavona R,Cimrman R,Hill DL,Chapelle D,Razavi R

    更新日期:2006-08-01 00:00:00

  • Quantitative analysis of multi-spectral fundus images.

    abstract::We have developed a new technique for extracting histological parameters from multi-spectral images of the ocular fundus. The new method uses a Monte Carlo simulation of the reflectance of the fundus to model how the spectral reflectance of the tissue varies with differing tissue histology. The model is parameterised ...

    journal_title:Medical image analysis

    pub_type: 杂志文章


    authors: Styles IB,Calcagni A,Claridge E,Orihuela-Espina F,Gibson JM

    更新日期:2006-08-01 00:00:00