Unified multiple‐feature color display for MR images

Kamman, R. L.; Stomp, G.P.; Berendsen, Herman J. C.

doi:10.1002/mrm.1910090209

Cited by 12 publications

(6 citation statements)

References 16 publications

(4 reference statements)

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“…The use of an achromatic intensity scale (gray scale) provides only one dimension for the latter purpose (7,8). Fortunately, the use of a chromatic (color) scale could provide three such dimensions, since three parameters are required to characterize a perceived color (8,9). Color scales are commonly used in many types of biomedical imaging and examples are given in Figure 1, where Figure 1a depicts the ''red temperature'' (top) and ''rainbow'' (bottom) scales, two of the approximately 40 provided in the IDL (Interactive Data Language) software package (Re-search Systems, Inc.; Boulder, CO).…”

Section: Color-scale Theory and Real-space Intimate Combinationmentioning

confidence: 99%

Intimate combination of low- and high-resolution image data: I. real-space PET and1H2O MRI, PETAMRI

et al. 1999

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Two different types of (co-registered) images of the same slice of tissue will generally have different spatial resolutions. The judicious pixel-by-pixel combination of their data can be accomplished to yield a single image exhibiting properties of both. Here, axial 18 FDG PET and 1 H 2 O MR images of the human brain are used as the low-and high-resolution members of the pair. A color scale is necessary in order to provide for separate intensity parameters from the two image types. However, not all color scales can accommodate this separability. The HSV color model allows one to choose a color scale in which the intensity of the low-resolution image type is coded as hue, while that of the high-resolution type is coded as value, a reasonably independent parameter. Furthermore, the high-resolution image must have high contrast and be quantitative in the same sense as the low-resolution image almost always is. Here, relaxographic MR images (naturally segmented quantitative 1 H 2 O spin-density components) are used. Their essentially complete contrast serves to effect an apparent editing function when encoded as the value of the color scale. Thus, the combination of 18 FDG PET images with gray-matter (GM) relaxographic 1 H 2 O images produces visually ''GM-edited'' 18 FDG PETAMR (positron emission tomography and magnetic resonance) images. These exhibit the high sensitivity to tracer amounts characteristic of PET along with the high spatial resolution of 1 H 2 O MRI. At the same time, however, they retain the complete quantitative measures of each of their basis images. Magn Reson Med 42:345-360,

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Section: Color-scale Theory and Real-space Intimate Combinationmentioning

confidence: 99%

Intimate combination of low- and high-resolution image data: I. real-space PET and1H2O MRI, PETAMRI

et al. 1999

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“…Many studies have demonstrated a variety of methods for producing color MR images [15,16,[21][22][23][24][25][26][27], with evidence to suggest these techniques have advantages for the reporting clinical radiologist over the traditional greyscale images. Over the last two decades image fusion techniques utilising color overlay to display more than one parameter have become commonplace in clinical radiology.…”

Section: Discussionmentioning

confidence: 99%

Color Fusion of Magnetic Resonance Images Improves Intracranial Volume Measurement in Studies of Aging

Hernández

Royle²,

Jackson³

et al. 2012

OJRad

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Background:Comparison of intracranial volume (ICV) measurements in different subpopulations offers insight into age-related atrophic change and pathological loss of neuronal tissue. For such comparisons to be meaningful the accuracy of ICV measurement is paramount. Color magnetic resonance images (MRI) have been utilised in several research applications and are reported to show promise in the clinical arena. Methods: We selected a sample of 150 older community-dwelling individuals (age 71 to 72 years) representing a wide range of ICV, white matter lesions and atrophy. We compared the extraction of ICV by thresholding on T2*-weighted MR images followed by manual editing (reference standard) done by an analyst trained in brain anatomy, with thresholding plus computational morphological operations followed by manual editing on a framework of a color fusion technique (MCMxxxVI) and two automatic brain segmentation methods widely used, these last three done by two image analysts. Results: The range of ICV was 1074 to 1921 cm 3 for the reference standard. The mean difference between the reference standard and the ICV measured using the technique that involved the color fusion was 2.7%, while it was 5.4% compared with any fully automatic technique. However, the 95% confidence interval of the difference between the reference standard and each method was similar: it was 7% for the segmentation aided by the color fusion and was 7% and 8.3% for the two fully automatic methods tested. Conclusion: For studies of aging, the use of color fusion MRI in ICV segmentation in a semi-automatic framework delivered best results compared with a reference standard manual method. Fully automated methods, while fast, all require manual editing to avoid significant errors and, in this post-processing step color fusion MRI is recommended.

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“…Kamman et al (4) reported an approach with parametric maps for obtaining a diagnostic characterization with colors. However, their chromatic characterization was different, since they used Tl and T2 maps to define the hue and saturation of each pixel.…”

Section: Discussionmentioning

confidence: 99%

Multiparametric display of spin‐echo data from MR studies of brain

Alfano¹,

Brunetti²,

Arpaia³

et al. 1995

Magnetic Resonance Imaging

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A magnetic resonance (MR) image processing technique that uses a single color image for simultaneous presentation of spin‐echo information and its application to MR studies of the brain is described. Relaxation rate and proton‐density maps were calculated from 160 brain MR studies performed at 1.5 and 1.0 T with standard spin‐echo sequences. Maps were fused into single color images, with R1, R2. and proton density coded, respectively, by red, green, and blue. The possibility of standardizing the technique was evaluated. Comparative analysis of color and conventional MR images of white matter disease and brain tumors was performed to assess intra‐ and interob‐server variability. Unequivocal and reproducible chromatic characterization of normal brain structures and a variety of lesions was obtained. Intra‐and interobserver analysis showed that color images can be used as a diagnostic tool. The technique may provide a simplified and timesaving approach for interpretation and presentation of brain MR studies.

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Unified multiple‐feature color display for MR images

Cited by 12 publications

References 16 publications

Intimate combination of low- and high-resolution image data: I. real-space PET and1H2O MRI, PETAMRI

Intimate combination of low- and high-resolution image data: I. real-space PET and1H2O MRI, PETAMRI

Color Fusion of Magnetic Resonance Images Improves Intracranial Volume Measurement in Studies of Aging

Multiparametric display of spin‐echo data from MR studies of brain

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