Fusion of coregistered cross-modality images using a temporally alternating display method

Evaluation of novel genetic algorithm generated schemes for positron emission tomography (PET)/magnetic resonance imaging (MRI) image fusion

The use and benefits of a multimodality approach in the context of breast cancer imaging are discussed. Fusion techniques that allow multiple images to be viewed simultaneously are discussed. Many of these fusion techniques rely on the use of color tables. A genetic algorithm that generates color tables that have desired properties such as satisfying the order principle, the rows, and columns principle, have perceivable uniformity and have maximum contrast is introduced. The generated 2D color tables can be used for displaying fused datasets. The advantage the proposed method has over other techniques is the ability to consider a much larger set of possible color tables, ensuring that the best one is found. We asked radiologists to perform a set of tasks reading fused PET/MRI breast images obtained using eight different fusion techniques. This preliminary study clearly demonstrates the need and benefit of a joint display by estimating the inaccuracies incurred when using a side-by-side display. The study suggests that the color tables generated by the genetic algorithm are good choices for fusing MR and PET images. It is interesting to note that popular techniques such as the Fire/Gray and techniques based on the HSV color space, which are prevalent in the literature and clinical practice, appear to give poorer performance.

Multiscaled combination of MR and SPECT images in neuroimaging: A simplex method based variable-weight fusion

Single-photon emission computed tomography (SPECT) images alone are difficult to understand in diagnosis, since anatomical structures are absent from the data. Studies on combination attempt to locate functional changes of the SPECT image by the magnetic resonance (MR) image. Due to the low similarity between original images, fused results are always darkened, obscured or loss some crucial anatomical structures. This paper has solved these problems by the variable-weight matrix which is estimated by minimizing the cost function using the simplex method. Under the generalized intensity-hue-saturation (GIHS) framework, the multiscaled analysis is presented for a better detail preservation. Besides, interactive approaches are discussed for the gradual variation between original images and the control of detail performance. The similarity assessment evaluates several different methods on a normal brain atlas. Two clips show the interactive property of the proposed method, while two medical cases demonstrate its clinical values. We conclude that the proposed method is superior to traditional methods, when considering the definition and the information capacity of fused results.

Fusion viewer: a new tool for fusion and visualization of multimodal medical data sets

A new application, Fusion Viewer, available for free, has been designed and implemented with a modular object-oriented design. The viewer provides both traditional and novel tools to fuse 3D data sets such as CT (computed tomography), MRI (magnetic resonance imaging), PET (positron emission tomography), and SPECT (single photon emission tomography) of the same subject, to create maximum intensity projections (MIP) and to adjust dynamic range. In many situations, it is desirable and advantageous to acquire biomedical images in more than one modality. For example, PET can be used to acquire functional data, whereas MRI can be used to acquire morphological data. In some situations, a side-by-side comparison of the images provides enough information, but in most of the cases it may be necessary to have the exact spatial relationship between the modalities presented to the observer. To accomplish this task, the images need to first be registered and then combined (fused) to create a single image. In this paper, we discuss the options for performing such fusion in the context of multimodal breast imaging. Additionally, a novel spline-based dynamic range technique is presented in detail. It has the advantage of obtaining a high level of contrast in the intensity range of interest without discarding the intensity information outside of this range while maintaining a user interface similar to the standard window/level windowing procedure.

Development and applications of a software for Functional Image Registration (FIRE)

Image registration with anatomical modalities, such as CT and MRI, facilitates the anatomical identification and localization in the interpretation of nuclear medicine images that lack anatomical information. The implementation of Functional Image Registration (FIRE), an operating system (OS) and platform independent multimodal image registration software is reported. In order to register the images without an operator's interaction, several automatic algorithms were implemented. These include principal axes matching and maximization of the mutual information methods. The user interface was designed to support the manual registration of the images. Fused images were composed by overlaying one image with the other one transparently, in which the opacity of the overlaid image was interactively controlled. FIRE was successfully applied to many clinical cases for which automatic and/or manual registration was required. An OS and platform independent program for image registration developed in this study will be useful for the clinical application of image registration techniques.