Generating Graphical Reports on Cardiac Catheterization

Igarashi, Yuriko; Igarashi, Takeo; Haraguchi, Ryo; Nakazawa, Kimitaka

doi:10.5772/54235

Cited by 3 publications

(2 citation statements)

References 12 publications

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“…As can be seen in [18], it has introduced a graphical report to record the procedure information (cardiac catheterization) related to AMI by using the coronary arteriogram. The coronary arteriogram can provide intuitive information on coronary anatomy and is generally used to record medical information, as shown in Fig.…”

Section: Coronary Arteriogrammentioning

confidence: 99%

“…A number of software programs developed in recent years reflect the distinctiveness of each modality of the medical images. For example, the graphical report has been introduced for effectively providing core information [18]. The graphical features allow a physician to more easily understand a report, but a lot of the features have limitations that are focused on analyzing a single modal medical image.…”

Section: Cardiac Pacsmentioning

confidence: 99%

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Analysis of Semantic Relations Between Multimodal Medical Images Based on Coronary Anatomy for Acute Myocardial Infarction

2015

J Inf Process Syst

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Acute myocardial infarction (AMI) is one of the three emergency diseases that require urgent diagnosis and treatment in the golden hour. It is important to identify the status of the coronary artery in AMI due to the nature of disease. Therefore, multi-modal medical images, which can effectively show the status of the coronary artery, have been widely used to diagnose AMI. However, the legacy system has provided multimodal medical images with flat and unstructured data. It has a lack of semantic information between multimodal images, which are distributed and stored individually. If we can see the status of the coronary artery all at once by integrating the core information extracted from multi-modal medical images, the time for diagnosis and treatment will be reduced. In this paper, we analyze semantic relations between multi-modal medical images based on coronary anatomy for AMI. First, we selected a coronary arteriogram, coronary angiography, and echocardiography as the representative medical images for AMI and extracted semantic features from them, respectively. We then analyzed the semantic relations between them and defined the convergence data model for AMI. As a result, we show that the data model can present core information from multi-modal medical images and enable to diagnose through the united view of AMI intuitively.

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Section: Coronary Arteriogrammentioning

confidence: 99%

Section: Cardiac Pacsmentioning

confidence: 99%

Analysis of Semantic Relations Between Multimodal Medical Images Based on Coronary Anatomy for Acute Myocardial Infarction

2015

J Inf Process Syst

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Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images

Chang,

Lin,

Wang

et al. 2024

Sci Rep

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Automated coronary angiography assessment requires precise vessel segmentation, a task complicated by uneven contrast filling and background noise. Our research introduces an ensemble U-Net model, SE-RegUNet, designed to accurately segment coronary vessels using 100 labeled angiographies from angiographic images. SE-RegUNet incorporates RegNet encoders and squeeze-and-excitation blocks to enhance feature extraction. A dual-phase image preprocessing strategy further improves the model's performance, employing unsharp masking and contrast-limited adaptive histogram equalization. Following fivefold cross-validation and Ranger21 optimization, the SE-RegUNet 4GF model emerged as the most effective, evidenced by performance metrics such as a Dice score of 0.72 and an accuracy of 0.97. Its potential for real-world application is highlighted by its ability to process images at 41.6 frames per second. External validation on the DCA1 dataset demonstrated the model's consistent robustness, achieving a Dice score of 0.76 and an accuracy of 0.97. The SE-RegUNet 4GF model's precision in segmenting blood vessels in coronary angiographies showcases its remarkable efficiency and accuracy. However, further development and clinical testing are necessary before it can be routinely implemented in medical practice.

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Template-Driven Medical Imaging Information Providing Process Using Semantic Relations Targeting Acute Myocardial Infarction

Park

Lee

2016

2016 10th International Conference on Innovative Mobile and Internet Services in Ubiquitous Computing (IMIS)

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Generating Graphical Reports on Cardiac Catheterization

Cited by 3 publications

References 12 publications

Analysis of Semantic Relations Between Multimodal Medical Images Based on Coronary Anatomy for Acute Myocardial Infarction

Analysis of Semantic Relations Between Multimodal Medical Images Based on Coronary Anatomy for Acute Myocardial Infarction

Optimizing ensemble U-Net architectures for robust coronary vessel segmentation in angiographic images

Template-Driven Medical Imaging Information Providing Process Using Semantic Relations Targeting Acute Myocardial Infarction

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