Department of IT Convergence Engineering, Kumoh National Institute of Technology (KIT), Gumi 39177, South Korea.
School of Electrical Engineering, Telkom University, Bandung 40257, Indonesia.
Comput Med Imaging Graph. 2021 Jun;90:101927. doi: 10.1016/j.compmedimag.2021.101927. Epub 2021 Apr 24.
In medical imaging and applications, efficient image sampling and transfer are some of the key fields of research. The compressed sensing (CS) theory has shown that such compression can be performed during the data retrieval process and that the uncompressed image can be retrieved using a computationally flexible optimization method. The objective of this study is to propose compressed medical imaging for a different type of medical images, based on the combination of the average sparsity model and reweighted analysis of multiple basis pursuit (M-BP) reconstruction methods, referred to as multiple basis reweighted analysis (M-BRA). The proposed algorithm includes the joint multiple sparsity averaging to improves the signal sparsity in M-BP. In this study, four types of medical images are opted to fill the gap of lacking a detailed analysis of M-BRA in medical images. The medical dataset consists of magnetic resonance imaging (MRI) data, computed tomography (CT) data, colonoscopy data, and endoscopy data. Employing the proposed approach, a signal-to-noise ratio (SNR) of 30 dB was achieved for MRI data on a sampling ratio of M/N=0.3. SNR of 34, 30, and 34 dB are corresponding to CT, colonoscopy, and endoscopy data on the same sampling ratio of M/N=0.15. The proposed M-BRA performance indicates the potential for compressed medical imaging analysis with high reconstruction image quality.
在医学成像和应用中，高效的图像采样和传输是研究的重点领域之一。压缩感知（CS）理论表明，这种压缩可以在数据检索过程中进行，并且可以使用计算灵活的优化方法检索未压缩的图像。本研究的目的是提出基于平均稀疏模型和加权分析多基追踪（M-BP）重建方法的组合的压缩医学成像，称为多基加权分析（M-BRA）。所提出的算法包括联合多稀疏平均，以提高 M-BP 中的信号稀疏性。在这项研究中，选择了四种类型的医学图像来填补 M-BRA 在医学图像中缺乏详细分析的空白。医学数据集包括磁共振成像（MRI）数据、计算机断层扫描（CT）数据、结肠镜检查数据和内窥镜检查数据。采用所提出的方法，在采样比 M/N=0.3 的情况下，MRI 数据的信噪比（SNR）达到 30dB。在相同的采样比 M/N=0.15 下，CT、结肠镜检查和内窥镜检查数据的 SNR 分别为 34、30 和 34dB。所提出的 M-BRA 性能表明了具有高重建图像质量的压缩医学成像分析的潜力。
