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Matching Methods
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- Interactive alignment by dragging images
- Automatic matching based on landmarks
- Automaic matching based
on pixel information, including Mutul Information
- Elastic normalization of brain images to an atlas
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| Fusion Features |
- Coupled 3D-cursor tracing
- Mixture of RGB contents
- Joint isocontour display
- Overlay pixels above a threshold on the other image
- Spy-glass window on
either image
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| Flexible Image Matching and Fusion Tool (PFUS) |
- Interactive and automatic image registration procedures
- Versatile image fusion and reporting features
- DICOM saving of fused images
- Pixel-wise image algebra
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 Brochure | User Guide |
[ Case Gallery - Cardiology]
[Cas Gallery - Preclinical Imaging] |
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| Bringing Multiple Studies into Alignment. Patients are often examined more than once, be it on separate systems or at different times during follow-up procedures. The most accurate approach to interpret the information contained in the result images is to transform them into a common coordinate system such that the organs get aligned and can be jointly reviewed. The present fusion tool supports this image matching task with several methods. Interactive matching is the universal solution. It allows an experienced physician to find a satisfactory match as long as there is sufficient anatomy in the images, even in multi-modality situations. When anatomical or fiducial landmarks are visible in both studies, corresponding points can be defined and then matched. With only a few assignments the studies can be brought into close alignment which can be interactively refined. Additionally, there are fully automatic methods which succeed if specific requirements are met. Principal axes matching and iterative methods using different comparison criteria including Mutual Information are available. As an extension to rigid matching, an elastic normalization algorithm is implemented for brain images. It is able to adjust the anatomy in an individual brain image to a suitable atlas image representing an “average” brain.. |
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| Explore Matched Images by Fusion Techniques. After matching, congruent images with equal resolution are available for joint exploration. A coupled 3D cursor allows to immediatly reslice orthogonal images at any point of the volume, and to compare the course of tissue boundaries. Fused images are always displayed in parallel. They can be configured in a multitude of ways including image mixing, contours, and overlays. A report form is available for documentation purposes, and the fused images can be sent into a DICOM archive as secondary capture objects. For quantitative analysis, volumes-of-interest can be directly outlined in the fused images, and statistics calculated in the original images. Furthermore, an algebra tool allows to perform operations with matched images in a similar way as a hand-held calculator. For instance, the perfusion reserve can be calculated as the difference between a stress and a rest study. As a further extension, the present fusion tool even supports mixing the information of three images into one fused representation. |
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| Additional Unique Features of the PMOD Fusion Tool |
- Motion correction of dynamic studies
- Image algebra in a hand-held calculater way
- Volume-of-interest definition in fused images and statistics of both studies
- Fusion of three studies simultaneously
- 2D and 3D correlation of pixel values in matched studies
- Batch mode for time-consuming matching operations
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Products 
Image Fusion]
