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Gates joint locally connected network for accurate and robust reconstruction in optical molecular tomography

Journal of Innovative optical Health Sciences 2024年第3期17卷 11-22页

作者： Minghua Zhao Yahui Xiao Jiaqi Zhang Xin Cao Lin Wang School of Computer Science and Engineering Xi’an University of TechnologyXi’anChina School of Information Science and Technology Northwest UniversityXi’an 710127China

optical molecular tomography(OMT)is a potential pre-clinical molecular imaging technique with applications in a variety of biomedical areas,which can provide non-invasive quantitative three-dimensional(3D)information regarding tumor distribution in living animals.The construction of optical transmission models and the application of reconstruction algorithms in traditional model-based reconstruction processes have affected the reconstruction results,resulting in problems such as low accuracy,poor robustness,and long-time consumption.Here,a gates joint locally connected network(GLCN)method is proposed by establishing the mapping relationship between the inside source distribution and the photon density on surface directly,thus avoiding the extra time consumption caused by iteration and the reconstruction errors caused by model inaccuracy.Moreover,gates module was composed of the concatenation and multiplication operators of three different gates.It was embedded into the network aiming at remembering input surface photon density over a period and allowing the network to capture neurons connected to the true source selectively by controlling three different gates.To evaluate the performance of the proposed method,numerical simulations were conducted,whose results demonstrated good performance in terms of reconstruction positioning accuracy and robustness.

关键词： optical molecular tomography gates module positioning accuracy robustness

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

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Artificial Intelligence in Medical Imaging 2020年第2期1卷 78-86页

作者： Xin Cao Kang Li Xue-Li Xu Karen M von Deneen Guo-Hua Geng Xue-Li Chen School of Information Science and Technology Northwest UniversityXi’an 710069Shaanxi ProvinceChina Engineering Research Center of molecular and Neuro Imaging Ministry of Educationand School of Life Science and TechnologyXidian UniversityXi’an 710126Shaanxi ProvinceChina

optical molecular tomography(OMT)is an imaging modality which uses an optical signal,especially near-infrared light,to reconstruct the three-dimensional information of the light source in biological tissue.With the advantages of being low-cost,noninvasive and having high sensitivity,OMT has been applied in preclinical and clinical research.However,due to its serious ill-posedness and illcondition,the solution of OMT requires heavy data analysis and the reconstruction quality is limited.Recently,the artificial intelligence(commonly known as AI)-based methods have been proposed to provide a different tool to solve the OMT problem.In this paper,we review the progress on OMT algorithms,from conventional methods to AI-based methods,and we also give a prospective towards future developments in this domain.

关键词： optical molecular tomography Deep learning Artificial intelligence Light propagation based algorithm Tomographic reconstruction

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