Inner Diameter Measurement Oriented Aortic Segmentation: An Edge Enhancement and Contextual Fusion Deep Learning Method

Author:

Zhang Di1ORCID,Zhang Wenjing1ORCID,Luo Tao1ORCID,Yang Ming2ORCID,Liu Aijun2ORCID

Affiliation:

1. Beijing University of Posts and Telecommunications, China

2. Capital Medical University, China

Publisher

ACM

Reference25 articles.

1. [ 1 ] Anderson K M , Odell P M , Wilson P W F, et al. Cardiovascular disease risk profiles[J]. American heart journal , 1991 , 121(1): 293-298. [1] Anderson K M, Odell P M, Wilson P W F, et al. Cardiovascular disease risk profiles[J]. American heart journal, 1991, 121(1): 293-298.

2. [ 2 ] Torok R D , Campbell M J , Fleming G A , Coarctation of the Aorta[M]//Diseases of the Aorta . Springer , Cham , 2019 : 111-125. [2] Torok R D, Campbell M J, Fleming G A, et al. Coarctation of the Aorta[M]//Diseases of the Aorta. Springer, Cham, 2019: 111-125.

3. [ 3 ] Yu Y , Gao Y , Wei J , A three-dimensional deep convolutional neural network for automatic segmentation and diameter measurement of type B aortic dissection[J]. Korean journal of radiology , 2021 , 22(2): 168. [3] Yu Y, Gao Y, Wei J, et al. A three-dimensional deep convolutional neural network for automatic segmentation and diameter measurement of type B aortic dissection[J]. Korean journal of radiology, 2021, 22(2): 168.

4. Aorta segmentation with a 3D level set approach and quantification of aortic calcifications in non-contrast chest CT[C]//2012 Annual International Conference of the IEEE Engineering;Kurugol S;Medicine and Biology Society. IEEE

5. Impact of Denoising on Deep-Learning-Based Automatic Segmentation Framework for Breast Cancer Radiotherapy Planning[J];Im J H;Cancers,2022

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