Luận án Tran Trung Nghia: Tái tạo ảnh 3D xuyên sáng động vật với giảm tán xạ

༤ኈㄽᩥ Realization of 3D image reconstruction from transillumination images of animal body ⏕య㏱どീ࠿ࡽࡢ 3D ീ෌ᵓᡂࡢᐇ⌧ ໭ᾏ㐨኱Ꮫ኱Ꮫ㝔᝟ሗ⛉Ꮫ◊✲⛉ TRAN TRUNG NGHIA 学 位 論 文 内 容 の 要 旨 博士の専攻分野の名称 博士（工学） 氏名 Tran Trung Nghia 学 位 論 文 題 名 Realization of 3D image reconstruction from transillumination images of animal body （生体透視像からの 3D 像再構成の実現） Three-dimensional (3D) imaging with X-ray or MRI has contributed greatly not only to medical diagnosis, but also to life science. The number of experimental animals killed for experimentation would be reduced if the animals internal structures can be visualized non-invasively. In transil- lumination imaging using near-infrared (NIR) light, the location of internal bleeding, infection, and angiogenesis can be visualized. Functional imaging is also possible using spectroscopic principles.

With specific contrast media, the usefulness of NIR imaging is expanded significantly. However, the NIR transillumination technique has not been used widely. The major reason for that relative lack of use is the difficulty of the strong scattering in tissues. In transillumination images, the deeper structure is blurred and cannot be differentiated from the shallower and less-absorbing structure.

To overcome this problem, great effort has been undertaken to develop optical computed tomography (optical CT) techniques. The typical technique for a macroscopic structure is diffuse optical tomography (DOT). Using this technique, cross-sectional imaging of human breasts and infant heads was achieved. Once the cross-sectional images become available, 3D imaging is possible.

However, current techniques require great computational effort such as finite element method calculation, and large devices such as numerous fiber bundles around the object body. It would be possible to reconstruct the 3D structure with a common filtered back-projection algo- rithm and with a CCD or CMOS camera if the scattering effect in transillumination images can be suppressed effectively. They require much simpler and more compact device as well as much less computational effort. This study proposes the 3D imaging of internal absorbing structure of a small experimental animal from two-dimensional (2D) NIR transillumination images using new scattering suppression techniques.

This thesis presents the principle, implementation, and the results to show the feasibility of the proposed method. For scattering suppression, the deconvolution technique using the point spread function (PSF) is effective. In previous study, the PSF for the light source located inside the medium had been derived by applying the diffusion approximation to the equation of transfer. With a known depth of the light source in a diffuse medium, the light distribution can be recovered clearly through an interstitial tissue by the deconvolution with this PSF.

Therefore, realization of the 3D imaging from the transillumina- tion images can be expected if this light-source PSF can be applied to the transillumination image of light-absorbing structure. Through theoretical and experimental study, the applicability of the PSF for the light source to the transillumination images of the light-absorbing structure was confirmed. The effectiveness of this technique was also confirmed in the experiments with a tissue-equivalent phantom and animal tissue. The PSF is depth-dependent, and the technique explained above was applicable only for an object with known internal structure.

To expand the applicability of this technique, new algorithms were devised. An observed transillumination image is deconvoluted with the PSFs of different depths. Then the deconvoluted images are summed up to produce a new image that serves as a projection image in cross-sectional reconstruction. The projection image contains the projection of the true absorption dis- tribution and the incompletely deconvoluted projection as well.

To suppress the effect of this erroneous projection, an erasing process was devised. An initial cross-sectional image is reconstructed from the projection images obtained from many orientations. It is used as a template to erase the erroneous dis- tribution in the cross-section. After the application of this erasing process, a new improved projection image is formed in which the effect of the erroneous distribution is suppressed effectively.

Using the projections from many orientations obtained in this process, an improved cross-sectional image can be reconstructed. With the cross-sectional images at different heights, the 3D image can be reconstructed. The feasibility of the proposed technique was examined in a computer simulation and an experiment with a model phantom. The results demonstrated the effectiveness of the proposed technique.

Finally, the applicability of the proposed technique to a living animal was examined. An anesthetized mouse was fixed in a transparent cylinder. To produce a transillumination image of good quality, a light trap in the cylinder was devised. Using the proposed technique, the 3D structure of the mouse abdomen was reconstructed.

High-absorbing organs such as the kidneys and parts of the liver became visible. Results of this study suggest that a new optical CT having different features from those of currently available techniques is possible. This simple system can provide a cross-sectional image and recon- struct the 3D structure of internal organ in the mouse body. It can provide a useful and safe tool for the functional imaging of internal organs of experimental animals and for optical CT imaging of the near-surface structure of a human body.

Table of contents Contents List of figures. iii Chapter 1 Introduction.1 Common small animal tomography imaging .3 PET and SPECT .2 Optical tomography imaging .1 Optical properties of biological tissue .3 Aims of the thesis.1 Computed tomography image reconstruction .1 Line integrals and projections .2 The Fourier slice theorem .3 Parallel-beam filtered back-projection .2 Radiative transport equation and diffusion equation .1 The radiative transfer equation .2 Depth-dependent point spread function for transcutaneous imaging .3 Lucy-Richardson deconvolution .1 Photon noise and image formation model .2 Lucy-Richardson deconvolution. 49 Chapter 4 Application of light source PSF to transillumination images .1 Theory of proposed technique .2 Applicability of light-source PSF to transillumination images of light-absorbing structure.3 Validation by simulation .4 Validation by experiment with tissue-equivalent phantom .5 Verification of scattering suppression with vessel model in tissue-equivalent medium using the n times deconvolution. 71 i Table of contents 4.6 Verification of the proposed technique with animal-tissue phantom.

78 Chapter 5 3D reconstruction of the known-structure transillumination images .1 3D reconstruction from transillumination images with tissue-equivalent phantom .2 3D reconstruction from transillumination images with animal-tissue phantom…. 89 Chapter 6 3D reconstruction of the unknown-structure transillumination images .1 3D reconstruction for unknown-structure transillumination images .2 Validation of the proposed technique in experiment. 97 Chapter 7 3D optical imaging of an animal body .1 Small animal transillumination imaging .2 3D optical small animal imaging. 105 Chapter 8 Preliminary study for more practical use .1 Depth estimation technique for transillumination image .1 Depth estimation technique .2 Validation of proposed technique in simulation .3 Validation in experiment with tissue-equivalent phantom.2 3D physiological function imaging for small animal using transillumination image.1 Method and experimental setup .2 Preliminary result in animal experiment.3 Scattering suppression technique for transillumination image using PSF derived for cylindrical scattering medium shape .1 Position-dependent PSF for cylindrical structure .2 Validation in experiment.

150 ii List of figures List of figures Fig. Small animal imaging modalities with typical instruments available and illustrative example images that can be obtained with these modalities: (a) micro-PET, (b) micro-CT, (c) micro-SPECT, (d) micro-MRI, (e) optical reflectance fluorescence imaging, (f) optical bioluminescence imaging. Scanning geometry: (a) rotation bed, (b) rotation gantry. Small animal computed tomography (CT): (a) schematic illustrating the principles of CT, (b) small animal CT axial images and 3D representation of tumor volumes in a genetically engineered mouse model of non-small-cell lung cancer.

Small animal magnetic resonance imaging (MRI): (a) schematic showing the basic principles of this technique, (b) Cross-sectional MRI images of the mouse, whereby the tumor is highlighted with an arrow. Small animal positron emission tomography (PET): (a) schematic illustrating the basic principles of PET, (b) images demonstrating the noninvasive visualization of an orthotopic brain tumor in a rat. Pinks arrows show the tumor, and the red arrow shows wound due to intracerebral implantation of tumor cells. Small animal single photon emission computed tomography (SPECT): (a) schematic illustrating the principles of SPECT, (b) SPECT images demonstrating the utility of visualizing gastrin-releasing peptide receptor in mice.

Arrows point to tumor. Optical fluorescence molecular imaging: (a) schematic illustrating the principle of molecular imaging using optical fluorescence, (b) fluorescence images. Optical bioluminescence molecular imaging: (a) schematic illustrating the principle of molecular imaging using optical bioluminescence, (b) bioluminescence images. Small animal imaging using diffuse optical tomography.

The absorption spectra of major tissue chromophores. Schematic rendering of different methods that can be used for whole-body fluorescence imaging: (a) broad beam illumination, (b) raster-scan illumination, (c) raster-scan illumination, (d) broad beam transillumination, (e) raster-scan transillumination, (f) raster-scan transillumination. The configurations optimized for iii List of figures tomography imaging and fiber-based planar configurations are not shown in this figure. The three imaging domains of optical imaging system: (a) continuous wave domain, (b) frequency domain, (c) time domain.

X-ray CT views. Computed tomography acquires a set of views and then reconstructs the corresponding image. Each sample in a view is equal to the sum of the image values along the ray that points to that sample. In this example, the image is a small pillbox surrounded by zeroes.

While only three views are shown here, a typical X-ray CT scan uses hundreds of views at slightly different angles. Example of simple back-projection. Back-projection reconstructs an image by taking each view and smearing it along the path it was originally acquired. The resulting image is a blurry version of the correct image.

The Fourier slice theorem relates the Fourier transform of a projection to the Fourier transform of the object along a radial line. The ideal filter response for filtered back-projection. Solid line: the Ram-Lak filter frequency response. Dashed line: resulting frequency response of the Ram-Lak filter multiplied by the Hamming function.

Example of using filtered back-projection technique. Filtered back-projection is reconstructing an image by filtering each view before back-projection. This removes the blurring seen in the simple back-projection as shown in Fig.2, and results in a mathematically exact reconstruction of the image. Specific intensity and the power dP given in Eq.

Principle of transcutaneous fluorescent imaging. Geometry of the theoretical model. Depth dependence of measured PSF spread. Diamonds and curve are the measurement and the theoretical calculation, respectively.

Example of the improvement of transcutaneous fluorescence image using depth-dependent PSF: (a) observed image, (b) depth-dependent PSF, (c) improved image. denotes the deconvolution operation. Geometry for PSF as light distribution observed at the scattering medium surface: (a) for fluorescence transcutaneous imaging, (b) for transillumination imaging. The orange circle denotes the light point sources in both cases.

Geometry for PSF as light distribution observed at the scattering medium iv List of figures surface in reality: (a) for fluorescence transcutaneous imaging, (b) for transillumination imaging. The orange circle denotes the light point sources in both cases. Procedure of proposed technique for transillumination image using light-source PSF. denotes the deconvolution operation.

Experimental setup for transillumination imaging: d = 4. Comparison of point spread function at depth d = 8.00 mm: (a) observed image with scattering medium, (b) observed image with transparent medium, (c) measured PSF from Eq.5), (d) light-source PSF from Eq. Intensity profiles along the centerlines of Figs. Comparison between theoretical PSF for light source and measured PSF for absorber.

Example of simulation process. u denotes the convolution operation. denotes the deconvolution operation. Result of the scattering suppression technique using light-source PSF at depth d = 2 mm.

Result of the scattering suppression technique using light-source PSF at depth d = 4 mm. Result of the scattering suppression technique using light-source PSF at depth d = 6 mm. Result of the scattering suppression technique using light-source PSF at depth d = 8 mm. Result of the scattering suppression technique using light-source PSF at depth d = 10 mm.

Comparison between the improved images by using proposed technique and using non-invert technique in terms of the spread (FWHM) of the absorber. Original image x of the absorbing object obtained with transparent medium. Result with transillumination image of the absorber at d =2. The intensity profiles show the distribution of light intensity along the dashed lines.