Wyniki wyszukiwania - BazTech

Ograniczanie wyników

1 Biocybernetics and Biomedical Engineering

1 2023

Znaleziono wyników: 1

Liczba wyników na stronie

Wyniki wyszukiwania

Wyszukiwano:
w słowach kluczowych: multidimensional fusion

Sortuj według:

Ogranicz wyniki do:

MDCF_Net: A Multi-dimensional hybrid network for liver and tumor segmentation from CT

Jiang Jian, Peng Yanjun, Hou Qingfan, Wang Jiao

Biocybernetics and Biomedical Engineering

2023

Vol. 43, no. 2

494--506

The segmentation of the liver and liver tumors is critical in the diagnosis of liver cancer, and the high mortality rate of liver cancer has made it one of the most popular areas for segmentation research. Some deep learning segmentation methods outperformed traditional methods in terms of segmentation results. However, they are unable to obtain satisfactory segmentation results due to blurred original image boundaries, the presence of noise, very small lesion sites, and other factors. In this paper, we propose MDCF_Net, which has dual encoding branches composed of CNN and CnnFormer and can fully utilize multidimensional image features. First, it extracts both intra-slice and inter-slice information and improves the accuracy of the network output by symmetrically using multidimensional fusion layers. In the meantime, we propose a novel feature map stacking approach that focuses on the correlation of adjacent channels of two feature maps, improving the network’s ability to perceive 3D features. Furthermore, the two coding branches collaborate to obtain both texture and edge features, and the network segmentation performance is further improved. Extensive experiments were carried out on the public datasets LiTS to determine the optimal slice thickness for this task. The superiority of the segmentation performance of our proposed MDCF_Net was confirmed by comparison with other leading methods on two public datasets, the LiTS and the 3DIRCADb.