Mengyu Jia

An endoscopic diffuse optical tomographic method based on the effective detection range

Endoscopic diffuse optical tomography (DOT) is a new medical imaging modality with the potential applications in functional imaging of the internal organs. To cut down the measurement time and the computation burden of image reconstruction, in this paper, we developed the image reconstruction algorithm with the partial measurement in the effective detection range (EDR) of a tubular tissue and the corresponding endoscopic imaging system with a novel endoscopic probe for flexibly selecting the detection sites. For a typical inner size and optical properties of the cervix, it is found that EDR is less than half of the inner circumference. Comparing to the traditional method, the adoption of EDR results in a reduction of more than a factor of two in the time cost for a measurement cycle and for the total iteration reconstruction. Images reconstructed from the simulation data demonstrate that the proposed method achieves equivalent image quality to that obtained from the complete data set. The images reconstructed from the EDR measurements on cervix-like solid phantoms show that both the location and size of the targets are reconstructed correctly. The proposed method will be useful to the development of endoscopic DOT technologies for cancer detection in tubular organs including cervix.

A modified laminar optical tomography system with small dip-angle and the initial validation

In a typical laminar optical tomography (LOT) system, the dip-angle between the incident light (or the emitting light) and the normal of the detection plane randomly changes during raster-scanning. The inconstant dip-angle causes consistency between the measurement and the light transportation model where a fixed dip-angle of the incident light is generally required. To eliminate the effect from this dip angle, methods such as keeping the angle unchangeable by moving the phantom instead of scanning the light were investigated. In this paper, a LOT system with small dip-angle over the whole detection range is developed. Simulation and experimental evaluation show that the dip-angle of the modified system is much smaller than that of the traditional system. For example, the relative angle between the two incident light at (x=0mm, y=0mm) and (x=0mm, y=2.5mm) on the image plane is about 0.7° for the traditional system while that is only about 0.02° for the modified system. The main parameters of the system are also evaluated and an image reconstruction algorithm is developed based on Monte Carlo simulation. The reconstructed images show that the spatial resolution and quantitative ratio is improved by the modified system without loss of the scanning speed.

Coupling between radiative transport and diffusion approximation for enhanced near-field photon-migration modeling based on transient photon kinetics

Coupling between transport theory and its diffusion approximation in subdomain-based hybrid models for enhanced description of near-field photon-migration can be computationally complex, or even physically inaccurate. We report on a physically consistent coupling method that links the transport and diffusion physics of the photons according to transient photon kinetics, where distribution of the fully diffusive photons at a transition time is provided by a computation- saving auxiliary time-domain diffusion solution. This serves as a complementary or complete isotropic source of the temporally integrated transport equation over the early stage and the diffusion equation over the late stage, respectively, fromwhich the early and late photodensities can be acquired independently and summed up to achieve steady-state modeling of the whole transport process. The proposed scheme is validated with numerical simulations for a cubic geometry.

Accelerating nonlinear reconstruction in laminar optical tomography by use of recursive SVD inversion

Image reconstruction in the most model-based biophotonic imaging modalities essentially poses an ill-posed nonlinear inverse problem, which has been effectively tackled in the diffusion-approximation-satisfied scenarios such as diffuse optical tomography. Nevertheless, a nonlinear implementation in high-resolution laminar optical tomography (LOT) is normally computationally-costly due to its strong dependency on a dense source-detector configuration and a physically-rigorous photon-transport model. To circumvent the adversity, we herein propose a practical nonlinear LOT approach to the absorption reconstruction. The scheme takes advantage of the numerical stability of the singular value decomposition (SVD) for the ill-posed linear inversion, and is accelerated by adopting an explicitly recursive strategy for the time-consuming repeated SVD inversion, which is based on a scaled expression of the sensitivity matrix. Experiments demonstrate that the proposed methodology can perform as well as the traditional nonlinear one, while the computation time of the former is merely 26.27% of the later on average.

Improvement of the background optical property reconstruction of the two-layered slab sample based on a region-stepwise-reconstruction method

Two-layered slab is a rational simplified sample to the near-infrared functional brain imaging using diffuse optical tomography (DOT).The quality of reconstructed images is substantially affected by the accuracy of the background optical properties. In this paper, region step wise reconstruction method is proposed for reconstructing the background optical properties of the two-layered slab sample with the known geometric information based on continuous wave (CW) DOT. The optical properties of the top and bottom layers are respectively reconstructed utilizing the different source-detector-separation groups according to the depth of maximum brain sensitivity of the source-detector-separation. We demonstrate the feasibility of the proposed method and investigate the application range of the source-detector-separation groups by the numerical simulations. The numerical simulation results indicate the proposed method can effectively reconstruct the background optical properties of two-layered slab sample. The relative reconstruction errors are less than 10% when the thickness of the top layer is approximate 10mm. The reconstruction of target caused by brain activation is investigated with the reconstructed optical properties as well. The quantitativeness ratio of the ROI is about 80% which is higher than that of the conventional method. The spatial resolution of the reconstructions (R) with two targets is investigated, and it demonstrates R with the proposed method is better than that with the conventional method as well.

An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening

The cervical cancer screening at a pre-cancer stage is beneficial to reduce the mortality of women. An opto-electronic joint detection system based on DSP aiming at early cervical cancer screening is introduced in this paper. In this system, three electrodes alternately discharge to the cervical tissue and three light emitting diodes in different wavelengths alternately irradiate the cervical tissue. Then the relative optical reflectance and electrical voltage attenuation curve are obtained by optical and electrical detection, respectively. The system is based on DSP to attain the portable and cheap instrument. By adopting the relative reflectance and the voltage attenuation constant, the classification algorithm based on Support Vector Machine (SVM) discriminates abnormal cervical tissue from normal. We use particle swarm optimization to optimize the two key parameters of SVM, i.e. nuclear factor and cost factor. The clinical data were collected on 313 patients to build a clinical database of tissue responses under optical and electrical stimulations with the histopathologic examination as the gold standard. The classification result shows that the opto-electronic joint detection has higher total coincidence rate than separate optical detection or separate electrical detection. The sensitivity, specificity, and total coincidence rate increase with the increasing of sample numbers in the training set. The average total coincidence rate of the system can reach 85.1% compared with the histopathologic examination.

A fast 3D image reconstruction method based on Monte-Carlo simulation for laminar optical tomography

Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique. Currently, the forward problem of LOT image reconstruction is generally solved on the basis of Monte-Carlo (MC) methods. However, considering the nonlinear nature of the image reconstruction in LOT, with the increasing number of source positions, methods based on MC takes too much computation time. Based on the scheme of trajectory translation and target voxel regression (TT&TVR) proposed by our group, this paper develops a fast 3D image reconstruction algorithm. The algorithm is applied to the absorption reconstruction of the layered inhomogeneous media. Results demonstrate that the reconstructing time is less than 15min with the X-Y-Z section of the sample subdivided into 50 × 50 × 10 voxels, and the target size and quantitativeness ratio can be obtained in a satisfying accuracy.

A laminar optical tomography system for the early cervical cancer diagnosis

Laminar optical tomography (LOT) is a new mesoscopic functional optical imaging technique, which is an extension of a confocal microscope and diffuse optical tomography to acquire both the coaxial and off-axis scattered light at the same time. In this paper, a LOT system with a larger detection area aiming at the in vivo detection of early cervical cancer is developed. The field of view of our system is 10 mm x 10 mm. In order to improve the image quality of the system, two methods were performed: the correction of image distortion and the restriction of returning light. The performance of the system with aperture stop was assessed by liquid phantom experiments. Comparing with the Monte Carlo simulation, the measurement results show that the average relative errors of eight different source-detector distances corresponding to 4 source points are lower than the errors of the system taking the frame of objective lens as the aperture stop by 5.7%， 4.8%，6.1%，6.1% respectively. Moreover, the experiment based on the phantom with specified structure and optical parameters to simulate the cervix demonstrates that the system perform well for the cervix measurement.

The ellipsoid parametric description for the shape-based image reconstruction algorithm of diffuse optical tomography

As a new non-invasive medical imaging technology, diffuse optical tomography (DOT) has received considerable attention that can provide vast quantities of functional information of tissues. The reconstruction problem of DOT is highly ill-posed, meaning that a small error in the measurement data can bring about drastic errors of the reconstruction optical properties. In this paper, the shape-based image reconstruction algorithm of DOT is proposed for reducing the ill-poseness under the assumption that the optical properties of target region distribute uniformly. Since some human organs and tumors can be simplified as an ellipsoid, in this paper, the shape of the inhomogeneity is described as an ellipsoid. In the forward problem, the boundary element method (BEM) is implemented to solve the continuous wave diffusion equation (DE). By the use of the ellipsoid parametric method, the description of the shape, location and optical properties of the inhomogeneity, and the value of the background could be realized with only a small number of parameters. In the inverse calculation, a Levenberg-Marquardt algorithm with line searching is implemented to solve the underlying nonlinear least-squares problem. Simulation results show that the algorithm developed in this paper is effective in reducing the ill-poseness and robust to the noise.