Optical detection software

Target

The overall function of the App of this project is to analyze the fluorescence signal and display the detection results. After the fluorescence image is obtained by the smartphone imaging system, the App needs to quantitatively analyze the image to obtain the fluorescence intensity information. The fluorescence information and miRNA concentration are then displayed at the interface. At the same time, the user can also interact with the App through the smartphone.

Function

(1) APP application technology

The software program is divided into a client-side App, a server, and a Python computing module.

The server uses Android Studio and Kotlin. The client uses IDEA, Java, and Spring. The python computing module uses PyCharm, NumPy, and PIL.

Fig.1 Technical process

(2) App menu and functions

The menu interface of the App includes a camera interface and a diagnostic result presentation interface. The camera interface mainly includes setting camera parameters, taking photos, and storing and displaying photos. The diagnostic results presentation interface includes displaying the received data and sending it to the mathematical model to show miRNA concentrations.

Fig. 2 (a) the camera interface ;(b) the diagnostic results presentation interface

(3) Fluorescence detection process

Fluorescence detection includes image acquisition, fluorescence region selection, fluorescence intensity measurement, and analysis of detection results. Image acquisition: Set the automatic acquisition of fluorescence images, pre-set the reaction time, and automatically collect images after reaching a certain time. Fluorescence region selection: When analyzing fluorescence images, the effective fluorescence regions are identified from the images. This can be achieved using automatic or manual identification. Fluorescence intensity measurement: Since the resulting fluorescence picture shows green fluorescence, we extract the green channel component from the fluorescence region, and directly analyze the content of green light in the photo to directly reflect the fluorescence intensity. Analysis of detection results: Based on the established mathematical model and the measured fluorescence intensity signal, the corresponding miRNA concentration is calculated and the detection results are obtained.

Fig.3 fluorescence detection process

(4) Usage process of App

  1. Open the App and grant the camera permission

  2. Adjust the parameters and position of the camera

  3. Click to take a picture

  4. Click the image preview button in the lower right corner to preview the captured picture

  5. Select the photos you want to perform fluorescence analysis and click on the lower right corner for analysis

  6. Jump to the result rendering interface to return the average G value of the image

Fig.4 Using process of APP
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Contributors: 林东方