A New Registration Approach for Dynamic Analysis of Calcium Signals in Organs
This work addresses a domain-specific challenge in biomedical imaging for researchers studying calcium signaling in organ development and disease, offering an incremental improvement over existing registration techniques.
The paper tackles the problem of aligning fruit fly wing disc pouches across image sequences for calcium signal analysis, where existing registration methods fail due to intensity oscillations, and presents a new two-phase non-rigid registration approach that significantly outperforms state-of-the-art methods.
Wing disc pouches of fruit flies are a powerful genetic model for studying physiological intercellular calcium ($Ca^{2+}$) signals for dynamic analysis of cell signaling in organ development and disease studies. A key to analyzing spatial-temporal patterns of $Ca^{2+}$ signal waves is to accurately align the pouches across image sequences. However, pouches in different image frames may exhibit extensive intensity oscillations due to $Ca^{2+}$ signaling dynamics, and commonly used multimodal non-rigid registration methods may fail to achieve satisfactory results. In this paper, we develop a new two-phase non-rigid registration approach to register pouches in image sequences. First, we conduct segmentation of the region of interest. (i.e., pouches) using a deep neural network model. Second, we obtain an optimal transformation and align pouches across the image sequences. Evaluated using both synthetic data and real pouch data, our method considerably outperforms the state-of-the-art non-rigid registration methods.