# Coregistration and Spatial Compounding of
## 3 Results  
OA data were acquired sequentially at several array positions and wavelengths; hence spatio-temporal discrepancies exist between the corresponding image sequences. Determination of the heart and breathing rates as well as phase information of the mouse heart is then essential for image compounding. Two prominent peaks in the low-frequency range of the temporal Fourier transform for a sequence of 1000 frames can clearly be distinguished (Figure 1b, top). These correspond to cardiac (7.1 Hz) and respiratory (2 Hz) rates, which are within the normal physiological range. The high-frame-rate of the OAT system (100 Hz) facilitates distinguishing all harmonic components corresponding to cardiac and respiratory motion, which would appear as alias frequencies if acquired at lower rates. The fundamental heart frequency can also be easily identified in the temporal Fourier transforms of a shorter sequence consisting of 100 frames (Figure 1b, bottom), which facilitates reducing the data required for effective compounding. Figure 1c shows three-dimensional views of three reconstructed OA images for 800 nm excitation at consecutive scanning positions in the vertical direction. It is shown that only a limited region of the heart can be effectively covered at each position. The corresponding phase maps for a given slice (indicated in Figure 1c) are displayed in Figure 1d. The difference in color distributions represents the phase shift between different sequences. Stitching was enabled by correcting the phase differences between consecutive scanning positions. This is illustrated in Figure 1d, where the central scanning position was taken as reference. Different heart structures are labelled in the combined phase map. Figure 2 displays maximum intensity projections (MIPs) along the depth direction of OA images of the mouse heart for 800 nm wavelength excitation. The enhanced FOV achieved by stitching multiple images is clearly illustrated by comparing the image corresponding to a single position of the array (Figure 2a) and the compounded image (Figure 2b). Both images correspond to a FOV of \(16\times 16\times 10\) mm\({}^{3}\). Only a part of the heart is visible in Figure 2a, and the image appears empty for regions outside the effective FOV of the array. Figure 2b shows that the whole heart can be visualized afterthe spatial compounding procedure. This image effectively covers a FOV of \(16\times 16\times 10\) mm\({}^{3}\), which makes possible to clearly visualize the whole heart and surrounding vascular networks. The outline of the heart, the left and right ventricles (LV and RV), the left and right atria (LA and RA) as well as the coronary artery (CA) are labeled in Figure 2b. Figure 2c showcases a series of consecutive full-view images exhibiting heart motion during the cardiac cycle, from which it was possible to distinguish representative behavior of the heart at systole and diastole. The heart motion is more clearly visualized in a movie available in the on-line version of the journal (see the supplementary) corresponding to a rotating view of the compounded image. The results obtained for the co-registration of multi-spectra OA images are shown in Figure 3. Figure 3a shows the MIPs along the depth direction of the OA images for a given position of the array as a function of excitation wavelength. Two representative time points corresponding to systole and diastole are shown. Physiological structures are labeled on the images. Generally, it is shown that the OA signal intensity increases with wavelength for structures containing highly oxygenated blood (e.g., the LA). The un-mixing results are displayed in Figure 3b. The images were normalized to the maximum signal intensity of the two components after un-mixing. As expected, it is shown that HbO\({}_{2}\) is the dominant component in all heart chambers, particularly in the LA. HbR was mainly detected in the RV as well as in vascular networks surrounding the heart. Figure 2: Spatial compounding of the entire heart volume for a raster-scan acquisition.