Morphing' Class Filter: An Interactive Tool for Continous Adjustment of Tissue Type Related Contrast
The Proposed Class Filter Increases Tissue Type Related Contrast in MR Images of Brain. during the First Phase of the Filtering Process Tissue Type Classes Are Defined. This is Done by Operator Intervention, or by a Semiautomatic Process based Either on a Supervised or Unsupervised Classifier, Respectively. during the Second Phase a Pixel Intensity Transform Makes Pixels of the Same Tissue Class Appear 'more Similar' While the Pixel Intensities of Different Classes Will Become 'more Different', in Effect Increasing the Tissue Type Related Contrast. for Example, Normal Mixture Cluster Analysis is Performed on an MR Image Set Obtained by Varying Pulse Sequence (PS) Parameters and Provides Unsupervised Definition of Classes While Taking Advantage of Much Greater Information Content of the Whole Image Set in Comparison to that of a Single Image. the Algorithm Permits Continuous Transition ('morphing') between the Original Image and the Tissue Classification Image that Has Been Calculated from the Input Image Set by Simple Sliding Cursor-Bar on the Computer Screen under the Physician's Control. Consequently, the Resulting Images Do Not Require Retraining of the Physician Who is Already Familiar with the Appearance of Standard MR Images and They Make Mental Integration of Information from a Large Input Image Set Possible and Easier.
J. J. Sychra et al., "Morphing' Class Filter: An Interactive Tool for Continous Adjustment of Tissue Type Related Contrast," Neurological Research, vol. 17, no. 3, pp. 185 - 189, Taylor and Francis Group; Taylor and Francis, Jan 1995.
The definitive version is available at https://doi.org/10.1080/01616412.1995.11740310
Keywords and Phrases
Class filter; synthetic images; tissue contrast
International Standard Serial Number (ISSN)
Article - Journal
© 2023 Taylor and Francis Group; Taylor and Francis, All rights reserved.
01 Jan 1995