A convolutional neural network for an automatic biopsy needle detection and segmentation on ultrasound images

Published: 01-07-2021| Version 2 | DOI: 10.17632/zk6scwv52p.2
Contributors:
,
Jacek Andrzejewski,

Description

The dataset contains a convolutional neural network (CNN) which was trained to segment a biopsy needle in 2D ultrasound images. Together with the network, source files of Matlab scripts and a few input images are provided. The files are enough to run experiments. See the `README' file for further instructions. The CNN structure and results ware described in the article "An automatic biopsy needle detection and segmentation on ultrasound images using a convolutional neural network" published by Ultrasonic Imaging in June 20201 (doi.org/10.1177/01617346211025267). It is a fully automatic method that uses a CNN to detect a biopsy needle in 2D ultrasound images. In the paper, the CNN architecture is described, which was trained using the adaptive moment estimation optimizer. The needle is eventually located in the image by applying the Radon transform.

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