Dissertation
Dissertation > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Information processing (information processing) > Pattern Recognition and devices > Image recognition device

Study on Integrated Visualization Methods for Biomedical Images

Author LiTianJie
Tutor WangYuanYuan
School Fudan University
Course Medical Electronics
Keywords integrated visualization generalized intensity-hue-saturation (GIHS) nonsubsampled contourlet transform (NSCT) variable weight gamma function thesimplex method color appearance model biomedical image
CLC TP391.41
Type PhD thesis
Year 2012
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Researches on biomedical imaging have been unfolding with the advent of new modalities, which provides new tools for the description of biological tissues. Integrated visualization benefits the fusion of multimodalities and facilitates the interpretation of new modalities for a wide range of applications. It is specifically designed to meet the requirements by using the characteristics of original images. This dissertation focuses on the crucial problems in three biomedical applications, when integrating the gray image and pseudo-color image.Combination of the fluorescent image and the phase contrast image is valuable for the localization and functional studies of the protein. The fused result aims to restrain the black background of the fluorescent image, and display a complete distribution of the targeted proteins with sufficient location information of subcelluar structures.In the view of transparency, a variable-weight method is proposed in the generalized intensity-hue-saturation frame. The intensity components of original images are first analyzed by the nonsubsampled contourlet transform (NSCT). Subsequently, the low-frequency coefficients are combined as the rule based on a piecewise function consisting in two Gamma functions, while the high-frequency coefficients are combined as the maximum selection rule.Using the Otsu method and the visual information fidelity (VIF), the region-based assessment of similarity is designed to reveal the similarity between the fused image and the original images. Validation experiments on117sets of Arabidopsis images are for two purposes:the impact of the multiscaled analysis in the fusion and the comparison among different methods of integrated visualization. It was demonstrated that the invariance and the design of true two-dimensional filters rather than the directionality attribute to the fused effect. Besides, both the quantitative results and the application examples demonstrated the superiority of the proposed method over the traditional ones.The single photon emission computed tomography (SPECT) image alone is difficult to understand and utilize, since anatomical structures are absent from the data. Integrated visualization attempts to locate functional information of the SPECT image by the structural information of the magnetic resonance (MR) image. The fused result aims to restrain the black background of SPECT, and display a complete distribution of functional variation with sufficient location information of anatomical structures.After approximating the weight by a polynomial function, integrated visualization can be regarded as a linear optimization problem in which the simplex method is applied to determine the coefficients of the weighting function. The rules are then proposed for the combination in the multiscaled spaces. Interactive approaches are designed for the gradual variation between original images with the global transparency, and the control of detail performance with the global high-frequency transparency.In the experiments, the weighting function was first estimated. Its shape had less restraints than that based on two Gamma functions proposed in the former application. The similarity assessment then evaluated several different methods on a normal brain atlas composed of29slices. The observations in the example matched the quantitative results, and demonstrated the superiority of the proposed method over the traditional methods. Two clips showed the interactive property of the proposed method, while two medical cases demonstrated its clinical values. Besides, two methods for designing the S-shaped weighting function were also compared, ie. the simplex method and the method based on two Gamma functions.Combined with the B-mode ultrasound image, the elastography image can be better understood and utilized, which also expands the application range of ultrasonic non-destructive examination. Except preserving the original styles of interpretation, the fused result also aims to improve the ability in expressing the original images, especially the low-frequency structures in the B-mode ultrasound image.The fused method is proposed based on the color prediction of the color appearance model. It additionally involves the pseudo-color display with uniform lightness. Here the formulae are exhaustively derived from the CIECAM02color attributes to the CIEXYZ color channels, after the assumption of the known attributes including lightness, hue and saturation.Based on different color spaces and the color appearance models, the distribution of color aggregations was studied in the experiment. It was concluded that the range of lightness was determined by the available color aggregation for the fused image, and the saturation controlled the resolution of hue and the range of lightness. The similarity assessment was performed on49sets of simulated images. Its result was reasonable, and thus revealed the effectiveness of the proposed method. Two medical cases demonstrated the clinical values of the proposed method and its superiority over the traditional methods. Besides, its feasibility in fusing two high-resolution structural images was preliminarily approved based on the simulated MRI data.

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