VascuSens

A python project to produce a visualisation of blockages in an artery, based on given data from SMART stents. The visualisation algorithms used are based off of the pyEIT open-source framework. The software uses electrical impedance data from 16 electrodes, 8 positive and 8 negative, to produce a 2D Electrical Impedance Tomography visualisation.

Installation

1. Clone the source code to your local machine using git:

   • If you don't have git installed on your machine press the following link to check/download git
   • Make sure you are running Python 3.10 with python --version. If not, all active releases can be found here
   • To clone the repository run the following code into your terminal:
     git clone https://github.com/StamTheo28/EIT-Imaging-Python.git
   • run pip install -r requirements.txt

   Alternatively, the source code zip file is available here.

2. Install the executable Version:
   Note The executable version works only on Windows 64-bit System

   • Download the VascuSens installer on your machine by clicking on this link and pressing download on the Windows 64-bit Installer on the latest release.
   • Run the msi installer that has just been downloaded
   • Choose the install location of the app on your local machine
   • At the chosen location, there will be a folder containing the executable file “VascuSensVis” and any data it needs. Do not remove the executable from the folder. Instead, create a shortcut on your desktop to the executable file, for example
   • To run the app, simply run the executable file or any shortcuts made to it

Documentation

The Documents section shows how you can use the software using the GUI or the terminal. All appropriate documentation/demos on how to use them are located in this link.

Data Format

The data used must have the specific format below:

• It must be a 33x80 xlsx file
• The first row must be the Frequency from 20-100HZ
• The other 32 rows for each column should be the impedance readings
• The order of which data should be stored are explained below:
  • Positive nodes are marked as A and negative nodes as B:
    
  • There order is:
    

Dependencies

Python 3.10 is required

Dependencies	Version
numpy	>= 1.19.1
scipy	>= 1.5.0
matplotlib	>= 3.3.2
pandas	>= 1.1.3
openpyxl
shapely
pyeit	== 1.1.6

Examples

Here are examples of the output of the software by using the two command line interface approaches
Note This requires you to clone the source code and cd into the /vascusense/ folder in your terminal

1. Using GUI option:

Run the main python script with the --gui option, as in the following command python main.py --gui

Example 1:

Example 2:

2. Using command line:

Run the main python script with optional arguments (note that INPUT_PATH is required), as in the following command python main.py -i [INPUT_PATH] -c [FREQUENCY] -b [BASELINE_PATH] -f [FLATTEN]

Example 1:

python main.py -i //data/Second_Set/Blockage_10.xlsx -c 20 -b //data/Second_Set/Baseline.xlsx

Example 2:

python main.py -i //data/Second_Set/Blockage_5.xlsx -c 20 -b //data/Second_Set/Baseline.xlsx -f 1

Current Development Team

Name	Student ID	Email	Customer Role	SCRUM Role
Luke Hopkins	*****	*****	Variable	Variable
Thomas McCausland	*****	*****	Variable	Variable
Yifei Yu	*****	*****	Variable	Variable
Stamatis Theocharous	*****	*****	Variable	Variable

Note: Customer Roles and SCRUM roles all vary between each Sprint in order for all members of the team to get hands-on experience in every role.