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13 March 2024 Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks
Farouk Nouizi, Gyanesh A. Shah, Janaki S. Saraswatula, Maha Algarawi, Rajas Rajendra Pathare, Yang Zhang, Hakan Erkol, Gultekin Gulsen
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Proceedings Volume 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences; 1285704 (2024) https://doi.org/10.1117/12.3003404
Event: SPIE BiOS, 2024, San Francisco, California, United States
Abstract
Photo-magnetic imaging (PMI) is a novel diffuse optical imaging technique used to recover high resolution images of the optical absorption coefficient of bio-tissue. It uses near-infrared laser light to slightly warm up the tissue and measures the induced temperature using magnetic resonance thermometry (MRT). The measured temperature maps are then converted into absorption maps using a dedicated PMI image reconstruction algorithm. We present a convolutional neural network -based image reconstruction algorithm that improves the accuracy of the recovered absorption maps while reducing the recovery time. This approach directly delineates the boundaries of tumors on the MRT maps. These boundaries are then used to generate soft a priori information that will be employed to constrain the standard PMI image reconstruction algorithm. We evaluate the performance of the algorithm using a tissue-like phantom with an inclusion representing the presence of a potential tumor. The obtained results show that our new method can delineate the tumor region with an accuracy of ~96%.
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Farouk Nouizi, Gyanesh A. Shah, Janaki S. Saraswatula, Maha Algarawi, Rajas Rajendra Pathare, Yang Zhang, Hakan Erkol, and Gultekin Gulsen "Improving the performance and convergence speed of photo magnetic imaging reconstruction algorithm using convolutional neural networks", Proc. SPIE 12857, Computational Optical Imaging and Artificial Intelligence in Biomedical Sciences, 1285704 (13 March 2024); https://doi.org/10.1117/12.3003404
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KEYWORDS
Reconstruction algorithms
Tumors
Absorption
Diffusion
Convolutional neural networks
Image processing
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