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Residual learning network for accurate and stable reconstruction in Cerenkov luminescence tomography
Predicting histopathological findings of gastric cancer via deep generalized multi-instance learning
In this paper, a reconstruction method named multipath subspace pursuit (MSP) is applied to solve the FMT problem. At the end of an iteration, the MSP method creates several candidate support set. Through evaluating the normal of final residual vector, the best candidate can be selected as the final support set. Then the support set is used for reconstructing sense matrix to achieve the goal of FMT reconstruction.
In order to verity the reconstruction result of the proposed MSP method, the simulated experiment of triple fluorescent sources and quantitative analyses of position error and relative intensity error for the experiment have been conducted. The MSP method obtains satisfactory results, and the source position error is below 1 mm. Moreover, the computation time of the MSP method is about one order of magnitude less than iterated shrinkage with the L1-norm (IS_L1) method. The MSP method not only can obtain the result of robustness but also can reduce the artifacts in the background. The above results revealed the MSP method for the potential FMT application.
Initially, the human glioma cell line U87MG-fLuc cells were cultured, and the orthotopic mouse brain tumor model was established. 10 days after the tumor cell implantation, the mice were divided into two groups including the TMZ group and the control group. The mice in the TMZ group were treated with Temozolomide with dosage of 50 mg/kg/day intraperitoneally for continuous 6 days, and the mice in the control group were treated with sterile saline at equal volume. The bioluminescence imaging (BLI) was acquired every 5 days for monitoring the therapeutic responses. A randomly enhanced adaptive subspace pursuit (REASP) algorithm is presented for bioluminescence tomography reconstruction. Basically, numerical experiments were used to validate the efficiency of the proposed method, and then the mice’s CT and BLI data were acquired to reconstruct BLT using the REASP algorithm.
The results in this study showed that the growth of glioma can be monitored from very early stage, and the TMZ treatment efficacy can be reliably and objectively assessed using BLT method. Our data demonstrated TMZ can effectively inhibit the tumor growth.
Methods: The SNS was mainly based on the technology of optical molecular imaging. A novel optical path has been designed in our hardware system and a feature-matching algorithm has been devised to achieve rapid fluorescence and color image registration fusion. Ten in vivo studies of SLN detection in rabbits using indocyanine green (ICG) and blue dye were executed for system evaluation and 8 breast cancer patients accepted the combination method for therapy.
Results: The detection rate of the combination method was 100% and an average of 2.6 SLNs was found in all patients. Our results showed that the method of using SNS to detect SLN has the potential to promote its application.
Conclusion: The advantage of this system is the real-time tracing of lymph flow in a one-step procedure. The results demonstrated the feasibility of the system for providing accurate location and reliable treatment for surgeons. Our approach delivers valuable information and facilitates more detailed exploration for image-guided surgery research.
In this study we present a pure optical bioluminescence tomographic system (POBTS) and a novel BLT method based on multi-view projection acquisition and 3D surface reconstruction. The POBTS acquired a sparse set of white light surface images and bioluminescent images of a mouse. Then the white light images were applied to an approximate surface model to generate a high quality textured 3D surface reconstruction of the mouse. After that we integrated multi-view luminescent images based on the previous reconstruction, and applied an algorithm to calibrate and quantify the surface luminescent flux in 3D.Finally, the internal bioluminescence source reconstruction was achieved with this prior information.
A BALB/C mouse with breast tumor of 4T1-fLuc cells mouse model were used to evaluate the performance of the new system and technique. Compared with the conventional hybrid optical-CT approach using the same inverse reconstruction method, the reconstruction accuracy of this technique was improved. The distance error between the actual and reconstructed internal source was decreased by 0.184 mm.
Automatic detection of retinal vascular bifurcations and crossovers based on isotropy and anisotropy
Meshless local Petrov-Galerkin method for bioluminescent photon propagation in the biological tissue
The design and implementation of a C++ toolkit for integrated medical image processing and analyzing
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