Full-range space-division multiplexing optical coherence tomography angiography

In this study, we demonstrated a full-range space-division multiplexing optical coherence tomography (FR-SDM-OCT) system. Utilizing the galvanometer-based phase modulation full-range technique, the total imaging range of FR-SDM-OCT can be extended to \u3e20 mm in tissue, with a digitizer sampling rate of 500 MS/s and a laser sweeping rate of 100 kHz. Complex conjugate terms were suppressed in FR-SDM-OCT images with a measured rejection ratio of up to ∼46 dB at ∼1.4 mm depth and ∼30 dB at ∼19.4 mm depth. The feasibility of FR-SDM-OCT was validated by imaging Scotch tapes and human fingernails. Furthermore, we demonstrated the feasibility of FR-SDM-OCT angiography (FR-SDM-OCTA) to perform simultaneous acquisition of human fingernail angiograms from four positions, with a total field-of-view of ∼1.7 mm × ∼7.5 mm. Employing the full-range technique in SDM-OCT can effectively alleviate hardware requirements to achieve the long depth measurement range, which is required by SDM-OCT to separate multiple images at different sample locations. FR-SDM-OCTA creates new opportunities to apply SDM-OCT to obtain wide-field angiography o

FlyNet 2.0: Drosophila heart 3D (2D + time) segmentation in optical coherence microscopy images using a convolutional long short-term memory neural network

A custom convolutional neural network (CNN) integrated with convolutional long short-term memory (LSTM) achieves accurate 3D (2D + time) segmentation in cross-sectional videos of the Drosophila heart acquired by an optical coherence microscopy (OCM) system. While our previous FlyNet 1.0 model utilized regular CNNs to extract 2D spatial information from individual video frames, convolutional LSTM, FlyNet 2.0, utilizes both spatial and temporal information to improve segmentation performance further. To train and test FlyNet 2.0, we used 100 datasets including 500,000 fly heart OCM images. OCM videos in three developmental stages and two heartbeat situations were segmented achieving an intersection over union (IOU) accuracy of 92%. This increased segmentation accuracy allows morphological and dynamic cardiac parameters to be better quantified