Joint Thresholding: An Adaptive Thresholding Approach Considering The Consistency of High-Dimensional Fluorescence Imaging Data

Fluorescence imaging is crucial in biological research, yet the challenge of quantification analysis persists. For high-dimensional fluorescence imaging data, one important reason causing unsatisfactory results is the oversight of data consistency. In this paper, we propose an adaptive thresholding approach, joint thresholding, enhancing thresholding performance by incorporating the data consistency as prior knowledge and maximizing the posterior probability of thresholds. We provide compelling evidence demonstrating the effectiveness and benefits of our method in both quantitative comparison and visual representation.