Literature DB >> 20426045

Statistical regularization of deformation fields for atlas-based segmentation of bone scintigraphy images.

Karl Sjöstrand1, Mattias Ohlsson, Lars Edenbrandt.   

Abstract

The construction and application of statistical models of deformations based on non-rigid image registration methods have gained recent popularity. This paper presents the application of such a model to restricting a general-purpose registration algorithm to anatomically plausible solutions. Specifically, the Morphon registration method is used for atlas-based segmentation of bone scintigraphy images. From a training set of 734 images, a model of characteristic deformation fields is built and used for regularizing the registration of 113 test images. Results show that around 300 training images and 30 principal modes are sufficient for building a useful model. The segmentation succeeded in 106 of 113 test images.

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Year:  2009        PMID: 20426045     DOI: 10.1007/978-3-642-04268-3_82

Source DB:  PubMed          Journal:  Med Image Comput Comput Assist Interv


  2 in total

1.  Comparison of skeletal segmentation by deep learning-based and atlas-based segmentation in prostate cancer patients.

Authors:  Kazuki Motegi; Noriaki Miyaji; Kosuke Yamashita; Mitsuru Koizumi; Takashi Terauchi
Journal:  Ann Nucl Med       Date:  2022-06-30       Impact factor: 2.258

Review 2.  Application of SPECT and PET / CT with computer-aided diagnosis in bone metastasis of prostate cancer: a review.

Authors:  Zhao Chen; Xueqi Chen; Rongfu Wang
Journal:  Cancer Imaging       Date:  2022-04-15       Impact factor: 5.605

  2 in total

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