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Interactive visual exploration of overlapping similar structures for three-dimensional microscope images.

Nakao M, Takemoto S, Sugiura T, Sawada K, Kawakami R, Nemoto T, Matsuda T - BMC Bioinformatics (2014)

Bottom Line: However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure.Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures.A direct editing interface is also provided to specify both the target region and structures with characteristic features, where all manual operations can be performed on the rendered image.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan. megumi@i.kyoto-u.ac.jp.

ABSTRACT

Background: Recent advances in microscopy enable the acquisition of large numbers of tomographic images from living tissues. Three-dimensional microscope images are often displayed with volume rendering by adjusting the transfer functions. However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure. Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures. In these cases, the transfer functions previously used fail to optimize image generation, making it difficult to explore the connectivity of these tissues.

Results: This paper proposes an interactive visual exploration method by which the transfer functions are modified locally and interactively based on multidimensional features in the images. A direct editing interface is also provided to specify both the target region and structures with characteristic features, where all manual operations can be performed on the rendered image. This method is demonstrated using two-photon microscope images acquired from living mice, and is shown to be an effective method for interactive visual exploration of overlapping similar structures.

Conclusions: An interactive visualization method was introduced for local improvement of visualization by volume rendering in two-photon microscope images containing regions in which linear nerve structures crisscross in a complex manner. The proposed method is characterized by the localized multidimensional transfer function and interface where the parameters can be determined by the user to suit their particular visualization requirements.

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Interactive visual exploration for overlapping white matter structures. Visualization results obtained using (a) and (b) 1D TF presets, (c)x0 and Ω set by the user, (d) the locally refined result and (e) effect of the configurable parameters α and β, wherein the sensitivity and locality of the exploration can be interactively adjusted based on user objectives.
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Fig5: Interactive visual exploration for overlapping white matter structures. Visualization results obtained using (a) and (b) 1D TF presets, (c)x0 and Ω set by the user, (d) the locally refined result and (e) effect of the configurable parameters α and β, wherein the sensitivity and locality of the exploration can be interactively adjusted based on user objectives.

Mentions: During the experiment, the region containing white matter is trimmed, and νeye at the time of rendering is set as the − z direction. Figure 5(a) and (b) shows visualization results with 1D TF presets. We are able to confirm that most of the linear structures are included within the image in the (x, y, z) = (1, 1, 0) direction, but linear structures in directions other than (1, 1, 0) also exist but cannot be visualized clearly. Here, the focus is on linear structures in the direction (1, −1, 0) within the red circle. In the visualization of Figure 5(a), many parts of the linear structures in the red frame have become transparent. In Figure 5(b), linear structures in the (1, 1, 0) direction occlude the structures within the red frame, making it difficult to distinguish them. We attempt to selectively visualize based on the orientation of the linear structures by using e′3 as the feature. Because e′3 represents the local orientation of the structure, it is better to use the inner product rather than the distance when calculating the dissimilarity dF. The expression for dF in this case is given asFigure 5


Interactive visual exploration of overlapping similar structures for three-dimensional microscope images.

Nakao M, Takemoto S, Sugiura T, Sawada K, Kawakami R, Nemoto T, Matsuda T - BMC Bioinformatics (2014)

Interactive visual exploration for overlapping white matter structures. Visualization results obtained using (a) and (b) 1D TF presets, (c)x0 and Ω set by the user, (d) the locally refined result and (e) effect of the configurable parameters α and β, wherein the sensitivity and locality of the exploration can be interactively adjusted based on user objectives.
© Copyright Policy - open-access
Related In: Results  -  Collection

License 1 - License 2
Show All Figures
getmorefigures.php?uid=PMC4279998&req=5

Fig5: Interactive visual exploration for overlapping white matter structures. Visualization results obtained using (a) and (b) 1D TF presets, (c)x0 and Ω set by the user, (d) the locally refined result and (e) effect of the configurable parameters α and β, wherein the sensitivity and locality of the exploration can be interactively adjusted based on user objectives.
Mentions: During the experiment, the region containing white matter is trimmed, and νeye at the time of rendering is set as the − z direction. Figure 5(a) and (b) shows visualization results with 1D TF presets. We are able to confirm that most of the linear structures are included within the image in the (x, y, z) = (1, 1, 0) direction, but linear structures in directions other than (1, 1, 0) also exist but cannot be visualized clearly. Here, the focus is on linear structures in the direction (1, −1, 0) within the red circle. In the visualization of Figure 5(a), many parts of the linear structures in the red frame have become transparent. In Figure 5(b), linear structures in the (1, 1, 0) direction occlude the structures within the red frame, making it difficult to distinguish them. We attempt to selectively visualize based on the orientation of the linear structures by using e′3 as the feature. Because e′3 represents the local orientation of the structure, it is better to use the inner product rather than the distance when calculating the dissimilarity dF. The expression for dF in this case is given asFigure 5

Bottom Line: However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure.Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures.A direct editing interface is also provided to specify both the target region and structures with characteristic features, where all manual operations can be performed on the rendered image.

View Article: PubMed Central - PubMed

Affiliation: Graduate School of Informatics, Kyoto University, Yoshida Honmachi, Sakyo, Kyoto, Japan. megumi@i.kyoto-u.ac.jp.

ABSTRACT

Background: Recent advances in microscopy enable the acquisition of large numbers of tomographic images from living tissues. Three-dimensional microscope images are often displayed with volume rendering by adjusting the transfer functions. However, because the emissions from fluorescent materials and the optical properties based on point spread functions affect the imaging results, the intensity value can differ locally, even in the same structure. Further, images obtained from brain tissues contain a variety of neural structures such as dendrites and axons with complex crossings and overlapping linear structures. In these cases, the transfer functions previously used fail to optimize image generation, making it difficult to explore the connectivity of these tissues.

Results: This paper proposes an interactive visual exploration method by which the transfer functions are modified locally and interactively based on multidimensional features in the images. A direct editing interface is also provided to specify both the target region and structures with characteristic features, where all manual operations can be performed on the rendered image. This method is demonstrated using two-photon microscope images acquired from living mice, and is shown to be an effective method for interactive visual exploration of overlapping similar structures.

Conclusions: An interactive visualization method was introduced for local improvement of visualization by volume rendering in two-photon microscope images containing regions in which linear nerve structures crisscross in a complex manner. The proposed method is characterized by the localized multidimensional transfer function and interface where the parameters can be determined by the user to suit their particular visualization requirements.

Show MeSH