Multimodal Medical Image Fusion aims to combine more than one image of the same or different modality to enhance the image content and provide more information about diseases. We performed a Systematic Literature Review according to the methodology outlined in Kitchenham Charter ...
There is a lack of systematic review that focuses explicitly on deep multimodal fusion for 2D/2.5D semantic image segmentation. In summary, the main contributions of this paper are as follows: The remainder of this paper is organized as follows. The background concepts of deep multimodal fusion...
Deep learning for pulmonary embolism detection on computed tomography pulmonary angiogram: a systematic review and meta-analysis Article Open access 04 August 2021 Introduction PE is associated with significant morbidity and mortality and accounts for more than 100,000 annual deaths in the United States...
Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines. NPJ Digit Med. 2020;3(1):1–9. Article Google Scholar Chen T, Guestrin C, XGBoost:. A Scalable Tree Boosting System. Proceedings of the 22nd ACM SIGKDD International...
A systematic review on automated clinical depression diagnosis ArticleOpen access20 November 2023 Multimodal mental state analysis Article16 April 2024 Automated facial video-based recognition of depression and anxiety symptom severity: cross-corpus validation ...
P. Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines. npj Digit. Med. 3, 136 (2020). Article Google Scholar Picard, M., Scott-Boyer, M. P., Bodein, A., Perin, O. & Droit, A. Integration strategies of multi...
- 《Medical Image Analysis》 被引量: 0发表: 2024年 Fusion of medical imaging and electronic health records using deep learning: a systematic review and implementation guidelines Advancements in deep learning techniques carry the potential to make significant contributions to healthcare, particularly in ...
In this work, we present a systematic literature review of multimodal event detection techniques. We describe how various techniques leverage information from different modalities through data fusion. We further propose a novel taxonomy of multimodal event detection techniques according to their temporal ...
Full size image Undertakings to characterize this literature have been performed by Huang et al.13, who performed a systematic review of deep learning fusion of imaging and EHR data in health. However, it was limited to EHR and imaging data and deep learning applications. A follow-up review ...
There is an emerging trend towards issues such as applying generative adversarial networks and contrastive learning for multimodal medical image fusion and synthesis and utilizing the combined spatiotemporal resolution of functional MRI and electroencephalogram in a data-centric manner. This study is ...