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Literature DB >> 20426191

Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

Yuanjie Zheng¹, Murray Grossman, Suyash P Awate, James C Gee.

Abstract

We propose to use the sparseness property of the gradient probability distribution to estimate the intensity nonuniformity in medical images, resulting in two novel automatic methods: a non-parametric method and a parametric method. Our methods are easy to implement because they both solve an iteratively re-weighted least squares problem. They are remarkably accurate as shown by our experiments on images of different imaged objects and from different imaging modalities.

Entities: Disease Gene Species

Mesh：

Year: 2009 PMID： 20426191 PMCID： PMC3673007 DOI： 10.1007/978-3-642-04271-3_103

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

7 in total

1. Adaptive fuzzy segmentation of magnetic resonance images.

Authors: D L Pham; J L Prince
Journal: IEEE Trans Med Imaging Date: 1999-09 Impact factor: 10.048

2. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.

Authors: Y Zhang; M Brady; S Smith
Journal: IEEE Trans Med Imaging Date: 2001-01 Impact factor: 10.048

3. Parametric estimate of intensity inhomogeneities applied to MRI.

Authors: M Styner; C Brechbühler; G Székely; G Gerig
Journal: IEEE Trans Med Imaging Date: 2000-03 Impact factor: 10.048

Review 4. A review of methods for correction of intensity inhomogeneity in MRI.

Authors: Uros Vovk; Franjo Pernus; Bostjan Likar
Journal: IEEE Trans Med Imaging Date: 2007-03 Impact factor: 10.048

5. A method for selecting the bin size of a time histogram.

Authors: Hideaki Shimazaki; Shigeru Shinomoto
Journal: Neural Comput Date: 2007-06 Impact factor: 2.026

6. Emergence of simple-cell receptive field properties by learning a sparse code for natural images.

Authors: B A Olshausen; D J Field
Journal: Nature Date: 1996-06-13 Impact factor: 49.962

7. A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

Authors: J G Sled; A P Zijdenbos; A C Evans
Journal: IEEE Trans Med Imaging Date: 1998-02 Impact factor: 10.048

7 in total

4 in total

Automatic correction of intensity nonuniformity from sparseness of gradient distribution in medical images.

1. Adaptive fuzzy segmentation of magnetic resonance images.

2. Segmentation of brain MR images through a hidden Markov random field model and the expectation-maximization algorithm.

3. Parametric estimate of intensity inhomogeneities applied to MRI.

Review 4. A review of methods for correction of intensity inhomogeneity in MRI.

5. A method for selecting the bin size of a time histogram.

6. Emergence of simple-cell receptive field properties by learning a sparse code for natural images.

7. A nonparametric method for automatic correction of intensity nonuniformity in MRI data.

1. Single-image vignetting correction from gradient distribution symmetries.

2. Planning of electroporation-based treatments using Web-based treatment-planning software.

3. Electroporation-based treatment planning for deep-seated tumors based on automatic liver segmentation of MRI images.

4. Segmentation of hepatic vessels from MRI images for planning of electroporation-based treatments in the liver.