Liandong Zhou, Computional Science & Engineering, Yonsei University Seoul, South Korea
We reconstructed conductivity changes of human lungs caused by breathing. “The Principal Component Analysis Based Local Reconstruction Method” was applied for lung EIT. Own Matlab GUI was developed which loads .txt data file exported from the Sciospec EIT16 device.
The main idea was to extract lung data from the measured data and to find the corresponding lung region. Low-pass filter and PCA were used which can be considered as machine learning techniques. The standard sensitivity method with Tikhonov regularization was used for reconstruction on the local region with the extracted data
The main idea was to extract lung data from the measured data and to find the corresponding lung region. Low-pass filter and PCA were used which can be considered as machine learning techniques. The standard sensitivity method with Tikhonov regularization was used for reconstruction on the local region with the extracted data.
Reconstruction results: (1st row: std; 2nd row: std+low; 3rd row: PCA-LRM)
- Client : Yonsei University Seoul
- Year : 2017
- We DID : Sciospec EIT16
- Partners : Liangdong Zhou
- Category: application note
- Tags: EIT , imaging , Impedance Tomography , lung monitoring , lung ventilation , MATLAB , real-time image reconstruction , Sciospec EIT16
