In this paper, we propose a convolution kernel formed by 3D Gabor filter to process vessel segmentation, as shown in Fig. 1.

We built Gabor ConvNet using Gabor convolution kernels and tested it using three vessel datasets. It scored 85.06%, 70.52% and 67.11%, respectively, ranking ...

A learnable Gabor Convolution kernel for vessel segmentation. https://doi.org/10.1016/j.compbiomed.2023.106892 ·. Journal: Computers in Biology and Medicine ...

This repository contains the implementation of a convolutional neural network used to segment blood vessels in retina fundus images.

Gabor convolution is a technique that integrates the interpretability of Gabor filters with the powerful learning capabilities of convolutional neural networks ...

The Gabor filter response is obtained by a 2D convolution operator with FFT computation in the frequency domain. Four scales (σ = 2, 3, 4, 5) are used in ...

A learnable Gabor Convolution kernel for vessel segmentation. C Chen, K Zhou, S Qi, T Lu, R Xiao. Computers in Biology and Medicine 158, 106892, 2023. 10, 2023.

Nov 24, 2023 · CNNs are widely used in retinal vessel segmentation due to their skill in learning automatically to extract features in retinal images. CNNs are ...

Therefore, many scholars have adopted the wavelet function as the kernel function of the first convolutional layer, endowing it with a locally interpretable ...

This study proposed a vessel segmentation method based on Gabor features. According to the eigenvector of Hessian matrix of each pixel in the image,