Microscopy Image Capture Using FPGA Data Segmentation
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Solution Overview
Problem
Current multi-sensor microscopy systems face delays in image capture and data transfer due to slow data transfer connections and synchronization challenges, especially in dynamic environments where sample movement and illumination changes are rapid, leading to inefficiencies in data processing and decision-making.
Innovation Solution
The system optimizes image acquisition by organizing data into small partial image frames for faster transfer and analysis, using co-optimized hardware and software to minimize delays, and employs a data transfer architecture with a single clock for synchronization across multiple camera units, enabling direct memory access and high-speed serial interfaces to reduce bottlenecks.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Speed
If data from multiple image sensors is transferred using traditional slow connections, then data transfer reliability is maintained, but image acquisition speed and processing efficiency deteriorate
Solution Approach 1:
The patent segments the image data from multiple sensors into smaller data packets that can be transferred in parallel through a network. Instead of transferring complete large-resolution images from each sensor sequentially, the images are divided into multiple smaller packets that can be simultaneously transmitted, reducing overall transfer time and enabling faster data acquisition.
Solution Approach 2:
The patent introduces a network as an intermediary between the image sensors and the processing system. Multiple image sensors connect to a network switch, which then distributes data to multiple receiving devices. This intermediary architecture enables parallel data transfer paths, significantly increasing the overall data throughput compared to traditional sequential connections.
2Measurement precision
If multiple independent CPUs are used for each image sensor, then measurement precision is improved, but synchronization difficulty increases
Solution Approach 1:
The patent merges the processing resources by having multiple image sensors share a common network infrastructure and centralized processing system. Instead of each sensor having its own independent CPU, the sensors transmit data through a network to shared processing resources, reducing synchronization complexity while maintaining the ability to process high-resolution images accurately.
Solution Approach 2:
The network switch and processing system serve multiple functions: they handle data from multiple different sensors, perform synchronization, route data to appropriate processing devices, and manage data flow. This universal architecture replaces multiple specialized independent CPU systems, reducing overall system complexity while maintaining precision.
3Reliability
If complete image frames are transferred before analysis, then data integrity is ensured, but processing time increases
Solution Approach 1:
The patent implements preliminary action by transferring data packets and beginning processing operations before the complete image frame is fully captured and transferred. The system starts analyzing data as it arrives in packets, rather than waiting for the entire image, enabling earlier intervention and faster overall processing while maintaining data integrity through the packetized transfer protocol.
Data Source
AI summary
A method to capture microscopy images from multiple image sensors and to relay them to one or more central processing units while minimizing delay in image capture can include the co-optimization of image acquisition hardware, data aggregation digital logic, firmware, and integration with data post processing on the central processing units. The methods can include organizing the incoming image data into data packets containing partial image frames, together with configuring the central processing units to be capable of analyzing the received partial image frames. The quick analysis of the images, e.g., on the partial image frames, can allow the computational system to rapidly respond to the captured images, such as to provide feed back on the captured images before the next images are to be captured.