AVRawRA – application for video raw record acquisition for neuroimaging and videoregistration research

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Abstract

Application for Video Raw Record Acquisition – AVRawRA [ɔːvˈrɔːrə], is a software designed for acquisition and recording video from the cameras into raw binary and compressed video formats. AVRawRA allows using a wide range of camera devices in various neuroimaging applications. That provides the benefit of usage of expensive video registration equipment for several tasks with single software. The concept of presented software allows adding any camera device without rebuilding of the main code pipeline. Presented software has a user-friendly interface with interactive elements for regulating parameters of acquisition and recording in real time, without stopping video stream. Simultaneous real-time visualization, analysis and recording can be performed without loss of the efficiency and missed frames. AVRawRA supports recordings from camera devices with both external and internal triggers. The size of the saved video file is not restricted by the recording time and is limited only by the space on the storage. Our software is perfectly suited both for the neuroimaging applications and experiments with supplementary videoregistration. To summarize, AVRawRA represents a universal platform for usage of various videoregistration devices, performing real-time analysis and high-speed recordings in raw and compressed video formats.

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About the authors

D. S. Suchkov

INSERM UMR1249, INMED, Aix-Marseille University

Author for correspondence.
Email: suchkov.dmitriy.ksu@gmail.com
France, Marseille

V. V. Shumkova

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

V. R. Sitdikova

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

V. M. Silaeva

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

A. E. Logashkin

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

A. R. Mamleev

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

Y. V. Popova

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

L. S. Sharipzyanova

Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
Russian Federation, Kazan

M. G. Minlebaev

INSERM UMR1249, INMED, Aix-Marseille University; Kazan Federal University

Email: suchkov.dmitriy.ksu@gmail.com
France, Marseille; Kazan, Россия

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Supplementary files

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2. Fig. 1. General view of the AVRawRA user interface. The following panels are presented: 1) “Camera setup” panel; 2) Real-time image visualization panel; 3) “Region of interest (ROI)” panel; 4) “Record control” panel; 5) “Real-time analysis” pane.

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3. Fig. 2. Real-time intensity analysis during recording with Qcam 1394 fast camera. Image display shows a single frame with an image of the rat skull surface under the green (525 nm) LED highlight. Real-time intensity analysis shows distribution of the pixel intensity for the current frame in the image display.

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4. Fig. 3. Real-time intensity analysis using Qcam 1394 fast camera with marked ROI to the video stream from Fig. 2. Image display shows a single frame with an image of the mouse skull surface under the green (525 nm) LED highlight. The ROI region was marked with a red contour using the “freehand” tool. Real-time intensity analysis shows distribution of the pixel intensity inside the ROI region. Frame rate is 36 frames per second.

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5. Fig. 4. Real-time intensity analysis using Qcam 1394 fast camera after setting ROI to the video stream from Fig.2. Frame was reduced using ROI from 348 × 260 pixels to 88 × 112 pixels. Frame rate is 50 frames per second.

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6. Fig. 5. Acquiring and recording with a web camera device (Logitech C270) to the compressed video format (AVI). In the right bottom corner an inset with a fragment of the recorded video file opened in the media player.

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