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Automatic detection of arterial input function in dynamic contrast enhanced MRI based on affinity propagation
Lin Shi1, Defeng Wang, Wen Liu
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, NT, Hong Kong SAR, P.R. China; Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen, Guangdong, P.R. China.
A new Fast-AP clustering method automatically detects the arterial input function (AIF) in DCE-MRI with high accuracy and efficiency. This robust technique significantly reduces computational cost compared to traditional methods.
Area of Science:
- Medical Imaging
- Biomedical Engineering
- Radiology
Background:
- Dynamic contrast-enhanced magnetic resonance imaging (DCE-MRI) is crucial for disease diagnosis.
- Accurate detection of the arterial input function (AIF) is essential for quantitative analysis in DCE-MRI.
- Current AIF detection methods can be computationally expensive and lack robustness.
Purpose of the Study:
- To develop an automatic and robust method for AIF detection in DCE-MRI.
- To achieve high detection accuracy with reduced computational cost.
- To evaluate the performance of the proposed method against existing techniques.
Main Methods:
- Developed an accelerated affinity propagation (Fast-AP) clustering algorithm for automatic AIF detection.
- Validated the Fast-AP method on DCE-MRI datasets from rat kidneys and human head and neck.
- Compared Fast-AP performance with original AP, K-means, and manual AIF detection.
Main Results:
- Fast-AP demonstrated high AIF detection accuracy, comparable to the original AP method.
- Fast-AP significantly reduced computational cost by 64-92% compared to AP.
- Fast-AP and AP methods showed superior robustness and insensitivity to initialization compared to K-means.
Conclusions:
- The Fast-AP method provides an accurate and efficient solution for automatic AIF detection in DCE-MRI.
- This approach offers a robust and computationally advantageous alternative for AIF quantification.
- The study highlights the potential of Fast-AP for improving DCE-MRI analysis workflows.
