A model for nonrigid mammogram registration using mutual information

Wirth, Michael A.; Narhan, Jay; Gray, Derek W. S.

doi:10.1007/978-3-642-59327-7_59

Cited by 5 publications

(4 citation statements)

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“…Control points were located randomly [25], manually [81], or automatically from edge features [70] or the breast contour [145]. The mapping functions reported include elastic body splines (EBS) [25], which evolved from the description of the equilibrium displacements of homogeneous isotropic elastic material subjected to a load, and TPS [145].…”

Section: Registration Of Mr Mammogramsmentioning

confidence: 99%

Breast image registration techniques: a survey

Guo

Sivaramakrishna²,

et al. 2006

Med Bio Eng Comput

122

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Breast cancer is the most common type of cancer in women worldwide. Image registration plays an important role in breast cancer detection. This paper gives an overview of the current state-of-the-art in the breast image registration techniques. For the intramodality registration techniques, X-ray, MRI, and ultrasound are the primary focuses of interest. Intermodality techniques will cover the combination of different modalities. Validation of breast registration methods is also discussed.

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Section: Registration Of Mr Mammogramsmentioning

confidence: 99%

Breast image registration techniques: a survey

Guo

Sivaramakrishna²,

et al. 2006

Med Bio Eng Comput

122

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“…However, its primary use is for registration, typically using affine transforms. [18] and [20], among others, use maximization of mutual information for nonrigid registration. They represent nonrigid registration using thin-plate splines, which do not preserve discontinuity.…”

Section: Mutual Informationmentioning

confidence: 99%

Visual correspondence using energy minimization and mutual information

Kim

Kolmogorov

Zabih

2003

Proceedings Ninth IEEE International Conference on Computer Vision

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“…Radiologists also regularly compare bilateral mammogram pairs during screening in search for breast asymmetry. The mostly used computer based techniques of bilateral comparison include thin-plate spline transformation and wavelet transformation [4,7].…”

Section: Introductionmentioning

confidence: 99%

Efficient textural model-based mammogram enhancement

Haindl

Reměs

2013

Proceedings of the 26th IEEE International Symposium on Computer-Based Medical Systems

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An efficient method for X-ray digital mammogram multi-view enhancement based on the underlying twodimensional adaptive causal autoregressive texture model is presented. The method locally predicts breast tissue texture from multi-view mammograms and enhances breast tissue abnormalities, such as the sign of a developing cancer, using the estimated model prediction error. The mammogram enhancement is based on the cross-prediction error of mutually registered left and right breasts mammograms or on the single-view model prediction error if both breasts' mammograms are not available.

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A model for nonrigid mammogram registration using mutual information

Cited by 5 publications

References 1 publication

Breast image registration techniques: a survey

Breast image registration techniques: a survey

Visual correspondence using energy minimization and mutual information

Efficient textural model-based mammogram enhancement

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