All Outputs (3)

Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review (2021)
Journal Article
Jathanna, N., Podlasek, A., Sokol, A., Auer, D., Chen, X., & Jamil-Copley, S. (2021). Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review. Cardiovascular Digital Health Journal, 2(6), S21-S29. https://doi.org/10.1016/j.cvdhj.2021.11.005

Background: Accurate, rapid quantification of ventricular scar using cardiac magnetic resonance imaging (CMR) carries importance in arrhythmia management and patient prognosis. Artificial intelligence (AI) has been applied to other radiological chall... Read More about Diagnostic utility of artificial intelligence for left ventricular scar identification using cardiac magnetic resonance imaging—A systematic review.

An efficient interactive multi-label segmentation tool for 2D and 3D medical images using fully connected conditional random field (2021)
Journal Article
Li, R., & Chen, X. (2022). An efficient interactive multi-label segmentation tool for 2D and 3D medical images using fully connected conditional random field. Computer Methods and Programs in Biomedicine, 213, Article 106534. https://doi.org/10.1016/j.cmpb.2021.106534

Objective: Image segmentation is a crucial and fundamental step in many medical image analysis tasks, such as tumor measurement, surgery planning, disease diagnosis, etc. To ensure the quality of image segmentation, most of the current solutions requ... Read More about An efficient interactive multi-label segmentation tool for 2D and 3D medical images using fully connected conditional random field.

FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation (2021)
Presentation / Conference Contribution
Lin, Q., Chen, X., Chen, C., & Garibaldi, J. M. (2021, July). FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation. Presented at IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2021), Luxembourg, Luxembourg

Convolutional neural networks (CNNs) have achieved the state-of-the-art performance in many application areas, due to the capability of automatically extracting and aggregating spatial and channel-wise features from images. Most recent studies have c... Read More about FuzzyDCNN: Incorporating Fuzzy Integral Layers to Deep Convolutional Neural Networks for Image Segmentation.