Abstract

In this paper, a bat-inspired high-resolution ultrasound 3D imaging system is presented. Live bats demonstrate that the properly used ultrasound can be used to perceive 3D space. With this in mind, a neural network referred to as a Bat-G network is implemented to reconstruct the 3D representation of target objects from the hyperbolic FM (HFM) chirped ultrasonic echoes. The Bat-G network consists of an encoder emulating a bat's central auditory pathway, and a 3D graphical visualization decoder. For the acquisition of the ultrasound data, a custom-made Bat-I sensor module is used. The Bat-G network shows the uniform 3D reconstruction results and achieves precision, recall, and F1-score of 0.896, 0.899 and 0.895, respectively. The experimental results demonstrate the implementation feasibility of a high-resolution non-optical sound-based imaging system being used by live bats.

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Bat-inspired imaging (Bat-I) sensor emits broadband FM signals and records echoes reflected from the target object. The recorded data transformed into spectrogram are fed into the Bat-G network for training and the network eventually infers the object’s 3D representation. In order to train the network, we have adopted a supervised learning algorithm and created 4-channel ultrasound echo dataset, ECHO-4CH (49 k data for training and 2.6 k data for evaluation). Each echo data consists of eight spectrograms (256^2 grayscale image) and one 3D ground-truth label (64^3 voxels). The detailed description of ECHO-4CH dataset is covered in the Bat-G net paper.

• Measurement list and File numbering:

ex) T000001_05_02_FU

T000001 : Measurement list filenum, (CUBE, Position 1)

05 : Clockwise angle 50deg

02 : Repeat count 2

FU : High frequency resolution spectrogram from Up-side microphone (T: high time resolution spectrogram, F: high frequency resolution spectrogram / U: up, D: down, L: left, R: right)

--> Unlisted filenumbers were excluded due to low SNR

• Citation:

If you use this ECHO-4CH dataset, please add a reference using this bibtex entry.

@inproceedings{hwang2019bat,

title={Bat-G net: Bat-inspired High-Resolution 3D Image Reconstruction using Ultrasonic Echoes},

author={Hwang, Gunpil and Kim, Seohyeon and Bae, Hyeon-Min},

booktitle={Advances in Neural Information Processing Systems},

pages={3720--3731},

year={2019}

}