Fig. 5: In vivo tumor morphology reconstruction of the FSH sensor array in mouse model. | npj Flexible Electronics

Fig. 5: In vivo tumor morphology reconstruction of the FSH sensor array in mouse model.

From: Conformal, ultrathin crystalline-silicon-based Hall sensor arrays with deep learning models for early-stage monitoring of three-dimensional tumor tissues

Fig. 5: In vivo tumor morphology reconstruction of the FSH sensor array in mouse model.

a Photographs of the tumors grown on the left side of the mouse over 14 days. b The in situ tumor CT results of the mouse on Days 1, 3, 7, and 14. c Reconstruction results of the tumor on Days 1, 3, 7, and 14 through the deep learning model. d The comparative results of the tumor height and volume from CT, caliper, and sensors with neural network. e The differences between the measured tumor height (HMea) and the predicted tumor height (HPre) through the neural network. f The differences between the measured tumor volume (VMea) and the predicted tumor volume (VPre) through the neural network. Here, SD stands for standard deviation, and the Mean ± 1.96 SD stands for limits of agreement.

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