ArticleIEEE transactions on medical imaging2020
Software-Based Phase Control, Video-Rate Imaging, and Real-Time Mosaicing With a Lissajous-Scanned Confocal Microscope.
Article in IEEE transactions on medical imaging, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 9 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
9 citing papers in PubMed.
- Vision Gaze-Driven Micro-Electro-Mechanical Systems Light Detection and Ranging Optimization.Research (Washington, D.C.) · 2025Article
- CRASH2p: Closed-loop Two Photon Imaging in a Freely Moving Animal.bioRxiv : the preprint server for biology · 2024Article
- Development of an Optoelectronic Integrated Sensor for a MEMS Mirror-Based Active Structured Light System.Micromachines · 2023Article
- Robust endoscopic image mosaicking via fusion of multimodal estimation.Medical image analysis · 2023Article
- Capacitive Sensing for 2-D Electrostatic MEMS Scanner in a Clinical Endomicroscope.IEEE sensors journal · 2022Article
- Improved sampling scheme for LiDAR in Lissajous scanning mode.Microsystems & nanoengineering · 2022Review
- Resonant scanning design and control for fast spatial sampling.Scientific reports · 2021Article
- Image processing metrics for phase identification of a multiaxis MEMS scanner used in single pixel imaging.IEEE/ASME transactions on mechatronics : a joint publication of the IEEE Industrial Electronics Society and the ASME Dynamic Systems and Control Division · 2021Article
- Real-time video mosaicking to guide handheld in vivo microscopy.Journal of biophotonics · 2020Article
Corrections and comments
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Authors and funding
9 authors.
Funding
Abstract
We present software-based methods for automatic phase control and for mosaicing high-speed, Lissajous-scanned images. To achieve imaging speeds fast enough for mosaicing, we first increase the image update rate tenfold from 3 to 30 Hz, then vertically interpolate each sparse image in real-time to eliminate fixed pattern noise. We validate our methods by imaging fluorescent beads and automatically maintaining phase control over the course of one hour. We then image fixed mouse brain tissues at varying update rates and compare the resulting mosaics. Using reconstructed image data as feedback for phase control eliminates the need for phase sensors and feedback controllers, enabling long-term imaging experiments without additional hardware. Mosaicing subsampled images results in video-rate imaging speeds, nearly fully recovered spatial resolution, and millimeter-scale fields of view.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.