Development of tomographic reconstruction for three-dimensional optical imaging: From the inversion of light propagation to artificial intelligence

Figure 1 Main flowchart of optical molecular tomography. 3D: Three-dimensional; MRI: Magnetic resonance imaging; OMT: Optical molecular tomography; XCT: X-ray computed tomography.

Figure 2 Reconstruction results with a priori information. A and B: The axial and sagittal views of single photon emission computed tomography/computed tomography imaging, and an implanted light source is inserted into a mouse; C: The axial-view result of the reconstructed source. These images are reproduced from[47].

Figure 3 Reconstruction results with posteriori information. A: The luminescence distribution in the body; B and C: The three-dimensional results and the results of the local enlarged image in the local area of the liver; C: The images of the capillary acquired using six filters; D, E: The trans-axial multispectral-Cerenkov luminescence tomography reconstructed image of the capillary filled with ³²P-ATP at a 9 mm depth. A and B are reproduced from[67], while C and D are reproduced from[62].

Figure 4 Structure of the networks used in optical molecular tomography reconstruction. A: Multilayer perceptron-based bioluminescence tomography reconstruction network reproduced from[72]; B: Convolutional neural network-recurrent neural network-based fluorescence molecular tomography (FMT) reconstruction framework reproduced from[74]; C: Multilayer fully-connected neural network based on Cerenkov luminescence tomography reproduced from[75]; D: K-nearest neighbor-based locally connected network based on FMT reproduced from[76].