Photoacoustic imaging(PAI),recognized as a promising biomedical imaging modality for preclinical and clinical studies,uniquely combines the advantages of optical and ultrasound imaging.Despite PAI’s great potential t...Photoacoustic imaging(PAI),recognized as a promising biomedical imaging modality for preclinical and clinical studies,uniquely combines the advantages of optical and ultrasound imaging.Despite PAI’s great potential to provide valuable biological information,its wide application has been hindered by technical limitations,such as hardware restrictions or lack of the biometric information required for image reconstruction.We first analyze the limitations of PAI and categorize them by seven key challenges:limited detection,low-dosage light delivery,inaccurate quantification,limited numerical reconstruction,tissue heterogeneity,imperfect image segmentation/classification,and others.Then,because deep learning(DL)has increasingly demonstrated its ability to overcome the physical limitations of imaging modalities,we review DL studies from the past five years that address each of the seven challenges in PAI.Finally,we discuss the promise of future research directions in DL-enhanced PAI.展开更多
基金supported in part by a grant from the National Research Foundation(NRF)of Korea,funded by the Ministry of Science and ICT(Grant Nos.2023R1A2C3004880,2021M3C1C3097624)a grant from the NRF,funded by the Ministry of Education(Grant No.2019H1A2A1076500)+4 种基金a grant from the Korea Medical Device Development Fund,funded by the Ministry of Trade,Industry and Energy(Grant Nos.9991007019,KMDF_PR_20200901_0008)a grant from the Basic Science Research Program,through the NRF,funded by the Ministry of Education(Grant No.2020R1A6A1A03047902)a grant from the Institute of Information&Communications Technology Planning&Evaluation(IITP),funded by the Korea government(MSIT)[Grant No.2019-0-01906,Artificial Intelligence Graduate School Program(POSTECH)]a grant from the Korea Evaluation Institute of Industrial Technology(KEIT),funded by the Korea government(MOTIE)the BK21 FOUR(Fostering Outstanding Universities for Research)project.
文摘Photoacoustic imaging(PAI),recognized as a promising biomedical imaging modality for preclinical and clinical studies,uniquely combines the advantages of optical and ultrasound imaging.Despite PAI’s great potential to provide valuable biological information,its wide application has been hindered by technical limitations,such as hardware restrictions or lack of the biometric information required for image reconstruction.We first analyze the limitations of PAI and categorize them by seven key challenges:limited detection,low-dosage light delivery,inaccurate quantification,limited numerical reconstruction,tissue heterogeneity,imperfect image segmentation/classification,and others.Then,because deep learning(DL)has increasingly demonstrated its ability to overcome the physical limitations of imaging modalities,we review DL studies from the past five years that address each of the seven challenges in PAI.Finally,we discuss the promise of future research directions in DL-enhanced PAI.
