Sequential shape similarity for active contour based left ventricle segmentation in cardiac cine MR image

Bi, Ke; Tan, Yue; Ke, Cheng; Chen, Qingfang; Wang, Yuanquan

doi:10.3934/mbe.2022074

Cited by 7 publications

(6 citation statements)

References 49 publications

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“…In this paper we apply to lightweight for shape and reliable, stable network scheme to serve computation for the 3D angle of pulmonary artery in heart and rapidly present the 3D angle model of pulmonary artery and its 3D angle degree value to users at browser side. We adopt voxelization processing to detect repetitive pairwise In our further research we will use medical big data and adopt machine learning [23,24] to discover the best angle of the pulmonary artery for preoperative planning and to improve cardiovascular image processing [25,26] along with diagnosis methods through convolutional neural network and stochastic pooling [27].…”

Section: Discussionmentioning

confidence: 99%

Automatic computation of 3D angle of pulmonary artery based on Web3D for preoperative planning in cardiac surgery

Tu,

Zhang,

Zhang

et al. 2024

Preprint

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This paper proposes Web3D technology to improve the general, popular computation method of the 2D angle of the pulmonary artery for preoperative planning of children’s congenital cardiopathy. First, the Web3D technology automatically computes the 3D angle of pulmonary artery to remove the complex process of manual computation of the 3D angle of the pulmonary artery from the 2D angle. Second, due to the adoption of lightweight data transmission technology the computed 3D angle of the pulmonary artery is shown to the front client in the browser in less than 5 seconds in the case of a single 3D angle computation. At last, we test and compare computations of the 3D angle of the pulmonary artery with the mainstream Materialise Mimics. The experimental comparison reveals that our computation precision of the 3D angle of the pulmonary artery is 95 percent through the application of Web3D technology.

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Section: Discussionmentioning

confidence: 99%

Automatic computation of 3D angle of pulmonary artery based on Web3D for preoperative planning in cardiac surgery

Tu,

Zhang,

Zhang

et al. 2024

Preprint

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“…Atlas-based methodologies are used to convert the segmentation problem into a registering problem [19,20]. Among the most recent research [21], ACM is applied to MICCAI 2009 cardiac dataset, another Global Local Region-Based ACM, in combination with watershed [22]. Similarly, a combination of extended random walk and high-speed random walk [23] and the ACM-based technique, along with region-based segmentation [24], obtained a good dice value of 0.986.…”

Section: Related Workmentioning

confidence: 99%

A Novel Light U-Net Model for Left Ventricle Segmentation Using MRI

et al. 2023

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MRI segmentation and analysis are significant tasks in clinical cardiac computations. A cardiovascular MR scan with left ventricular segmentation seems necessary to diagnose and further treat the disease. The proposed method for left ventricle segmentation works as a combination of the intelligent histogram-based image enhancement technique with a Light U-Net model. This technique serves as the basis for choosing the low-contrast image subjected to the stretching technique and produces sharp object contours with good contrast settings for the segmentation process. After enhancement, the images are subjected to the encoder–decoder configuration of U-Net using a novel lightweight processing model. Encoder sampling is supported by a block of three parallel convolutional layers with supporting functions that improve the semantics for segmentation at various levels of resolutions and features. The proposed method finally increased segmentation efficiency, extracting the most relevant image resources from depth-to-depth convolutions, filtering them through each network block, and producing more precise resource maps. The dataset of MICCAI 2009 served as an assessment tool of the proposed methodology and provides a dice coefficient value of 97.7%, accuracy of 92%, and precision of 98.17%.

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“…A technique proposed in [19] to increase the precision of segmentation results and accuracy, the primary design agent for the segmentation work is carried out through the MRF-driven technique. This article shows the perfect result of the multi-agent system for remote sensing picture segmentation.…”

Section: Review Finding On Mas In Medical Imagementioning

confidence: 99%

A Review of Medical Image Techniques and Methods based on a Multi-agent System

Nayyef¹,

Sulaiman²,

Hasan³

et al. 2022

TEM Journal

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In cases where the success of artificial intelligence (AI) approaches is more focused on the multi-agent system (MAS) than those that may make AI understandable to humans, in light of the repetitive cycles of the history of AI, we expect to see technology reevaluation that is commonly referred to as 'classical IA' – especially agent and MAS – in the upcoming years. Other than that, agents and multi-agent (MAS) systems are crucial to designing intelligent systems from the start. They can open new possibilities to researchers for explanatory and intelligent systems through their long-term link with logical technology, which is characteristic of its early times. That is why it is now crucial to comprehend the present position of MAS for medical image methods. This paper thus seeks to provide a complete overview by reviewing the MAS and the agent approaches. Two different views are taken and assessed for the resulting technologies: the MAS and the image processing technologies.

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Sequential shape similarity for active contour based left ventricle segmentation in cardiac cine MR image

Cited by 7 publications

References 49 publications

Automatic computation of 3D angle of pulmonary artery based on Web3D for preoperative planning in cardiac surgery

Automatic computation of 3D angle of pulmonary artery based on Web3D for preoperative planning in cardiac surgery

A Novel Light U-Net Model for Left Ventricle Segmentation Using MRI

A Review of Medical Image Techniques and Methods based on a Multi-agent System

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