Computationally efficient nonlinear edge preserving smoothing of n-D medical images via scale-space fingerprint analysis

Reutter, B.W.; Algazi, V. Ralph; Huesman, R.H.

doi:10.1109/nssmic.2000.950121

Cited by 3 publications

(3 citation statements)

References 7 publications

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“…This small-scale transversely isotropic smoothing improved lung surface segmentations in simulated respiratory gated cardiac PET transmission images (Figure 3), compared to segmentations that we obtained previously (Ref. 7, Fig. 2, page 436).…”

Section: Effects Of Small-scale Transversely Isotropic Smoothingsupporting

confidence: 49%

“…We use recursive multiscale blending 6,7 to perform nonlinear edge preserving smoothing along 1-D profiles:…”

Section: Preserving 1-d Edges Via Recursive Multiscale Blendingmentioning

confidence: 99%

“…6,7 Analysis of time sequences of volumetric images (i.e., 4-D data) is decomposed into independent 1-D problems. Smoothing in various directions along 1-D profiles through 4-D data is driven by a measure of local structure separation seen in the scale-space fingerprint, rather than by a local contrast measure.…”

mentioning

confidence: 99%

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Edge-preserving smoothing and segmentation of 4D images via transversely isotropic scale-space processing and fingerprint analysis

et al. 2004

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Enhancements are described for an approach that unifies edge preserving smoothing with segmentation of time sequences of volumetric images, based on differential edge detection at multiple spatial and temporal scales. Potential applications of these 4-D methods include segmentation of respiratory gated positron emission tomography (PET) transmission images to improve accuracy of attenuation correction for imaging heart and lung lesions, and segmentation of dynamic cardiac single photon emission computed tomography (SPECT) images to facilitate unbiased estimation of time-activity curves and kinetic parameters for left ventricular volumes of interest. Improved segmentation of lung surfaces in simulated respiratory gated cardiac PET transmission images is achieved with a 4-D edge detection operator composed of edge preserving 1-D operators applied in various spatial and temporal directions. Smoothing along the axis of a 1-D operator is driven by structure separation seen in the scale-space fingerprint, rather than by image contrast. Spurious noise structures are reduced with use of small-scale isotropic smoothing in directions transverse to the 1-D operator axis. Analytic expressions are obtained for directional derivatives of the smoothed, edge preserved image, and the expressions are used to compose a 4-D operator that detects edges as zero-crossings in the second derivative in the direction of the image intensity gradient. Additional improvement in segmentation is anticipated with use of multiscale transversely isotropic smoothing and a novel interpolation method that improves the behavior of the directional derivatives. The interpolation method is demonstrated on a simulated 1-D edge and incorporation of the method into the 4-D algorithm is described.

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Section: Effects Of Small-scale Transversely Isotropic Smoothingsupporting

confidence: 49%

“…We use recursive multiscale blending 6,7 to perform nonlinear edge preserving smoothing along 1-D profiles:…”

Section: Preserving 1-d Edges Via Recursive Multiscale Blendingmentioning

confidence: 99%