TY - GEN
T1 - Screening of Dementia on OCTA Images via Multi-projection Consistency and Complementarity
AU - Wang, Xingyue
AU - Li, Heng
AU - Xiao, Zunjie
AU - Fu, Huazhu
AU - Zhao, Yitian
AU - Jin, Richu
AU - Zhang, Shuting
AU - Kwapong, William Robert
AU - Zhang, Ziyi
AU - Miao, Hanpei
AU - Liu, Jiang
N1 - Publisher Copyright:
© 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
PY - 2022
Y1 - 2022
N2 - It has been suggested that the retinal vasculature alternations are associated with dementia in recent clinical studies, and the eye examination may facilitate the early screening of dementia. Optical Coherence Tomography Angiography (OCTA) has shown its superiority in visualizing superficial vascular complex (SVC), deep vascular complex (DVC), and choriocapillaris, and it has been extensively used in clinical practice. However, the information in OCTA is far from fully mined by existing methods, which straightforwardly analyze the multiple projections of OCTA by average or concatenation. These methods do not take into account the relationship between multiple projections. Accordingly, a Multi-projection Consistency and complementarity Learning Network (MUCO-Net) is proposed in this paper to explore the diagnosis of dementia based on OCTA. Firstly, a consistency and complementarity attention (CsCp) module is developed to understand the complex relationships among various projections. Then, a cross-view fusion (CVF) module is introduced to combine the multi-scale features from the CsCp. In addition, the number of input flows of the proposed modules is flexible to boost the interactions across the features from different projections. In the experiment, MUCO-Net is implemented on two OCTA datasets to screen for dementia and diagnose fundus diseases. The effectiveness of MUCO-Net is demonstrated by its superior performance to state-of-the-art methods.
AB - It has been suggested that the retinal vasculature alternations are associated with dementia in recent clinical studies, and the eye examination may facilitate the early screening of dementia. Optical Coherence Tomography Angiography (OCTA) has shown its superiority in visualizing superficial vascular complex (SVC), deep vascular complex (DVC), and choriocapillaris, and it has been extensively used in clinical practice. However, the information in OCTA is far from fully mined by existing methods, which straightforwardly analyze the multiple projections of OCTA by average or concatenation. These methods do not take into account the relationship between multiple projections. Accordingly, a Multi-projection Consistency and complementarity Learning Network (MUCO-Net) is proposed in this paper to explore the diagnosis of dementia based on OCTA. Firstly, a consistency and complementarity attention (CsCp) module is developed to understand the complex relationships among various projections. Then, a cross-view fusion (CVF) module is introduced to combine the multi-scale features from the CsCp. In addition, the number of input flows of the proposed modules is flexible to boost the interactions across the features from different projections. In the experiment, MUCO-Net is implemented on two OCTA datasets to screen for dementia and diagnose fundus diseases. The effectiveness of MUCO-Net is demonstrated by its superior performance to state-of-the-art methods.
KW - Deep learning
KW - Dementia
KW - Multi-projection
KW - OCTA
UR - http://www.scopus.com/inward/record.url?scp=85139010248&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-16434-7_66
DO - 10.1007/978-3-031-16434-7_66
M3 - Conference contribution
AN - SCOPUS:85139010248
SN - 9783031164330
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 688
EP - 698
BT - Medical Image Computing and Computer Assisted Intervention – MICCAI 2022 - 25th International Conference, Proceedings
A2 - Wang, Linwei
A2 - Dou, Qi
A2 - Fletcher, P. Thomas
A2 - Speidel, Stefanie
A2 - Li, Shuo
PB - Springer Science and Business Media Deutschland GmbH
T2 - 25th International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2022
Y2 - 18 September 2022 through 22 September 2022
ER -