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Learning to Complement with Multiple Humans (LECOMH): Integrating Multi-rater and Noisy-Label Learning into Human-AI Collaboration
The advent of learning with noisy labels (LNL), multi-rater learning, and human-AI collaboration has revolutionised the development of robust classifiers, enabling them to address the challenges posed by different types of data imperfections and complex decision processes commonly encountered in real-world applications.
Automatic Delineation of Kidney Region in DCE-MRI
To address this issue, we present Dynamic Mode Decomposition (DMD) coupled with thresholding and blob analysis as a framework for automatic delineation of the kidney region.
Functional Segmentation through Dynamic Mode Decomposition: Automatic Quantification of Kidney Function in DCE-MRI Images
Traditionally, human experts are required to manually delineate the kidney ROI across multiple images in the dynamic sequence.
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