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A novel method of compressive sensing MRI reconstruction based on sandpiper optimization algorithm (SPO) and mask region based convolution neural network (mask RCNN)

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Abstract

A compressive sensing method is a current structure for signal sampling and reclamation. It allows signal acquisition with fewer sampling than the Nyquist-Shannon theorem needs and decreases Magnetic Resonance Imaging (MRI) data achievement time. In this manuscript, Mask Region Based Convolution Neural Network (Mask RCNN) optimized with Sand Piper Optimization (SPO) algorithm is proposed for eliminating aliasing artifacts while attaining enhanced reconstructing images. Initially, Mask Region Based Convolution Neural Network reduces the aliasing artifacts, and then Sand Piper Optimization is used to optimize the weight parameter of the Mask Region Based Convolutional Neural Network, which is used for enhancing the efficiency of image reconstruction. The advantage of Sandpiper Optimization Algorithm is to provide correct reconstruction from a small set of l-space. This algorithm prevents premature convergence and makes better solutions. The proposed algorithm is tested with compressive sensed l-space data at sampling rates 75%, 60% and 50%. Here, two different sampling methods are used, they are Cartesian and radial sampling. The simulation is carried out in MATLAB tool. Finally, the performance of the proposed method is analysed with Peak Signal to Noise Ratio (PSNR), Mean Square Error (MSE) and Structural Similarity Index Measure (SSIM) of brain and compared with five different existing methods.

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Data sharing does not apply to this article as no new data has been created or analyzed in this study.

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Authors and Affiliations

  1. Research Scholar, Department of Electronics and Communication Engineering, JNTUK, Kakinada, Andhra Pradesh, India

    Tirugatla Surya Kavitha

  2. Retired Professor, Department of Electronics and Communication Engineering, JNTUK, Kakinada, Andhra Pradesh, India

    Dr. Kodati Satya Prasad

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  1. Tirugatla Surya Kavitha
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  2. Dr. Kodati Satya Prasad
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Correspondence to Tirugatla Surya Kavitha.

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Kavitha, T.S., Prasad, D.S. A novel method of compressive sensing MRI reconstruction based on sandpiper optimization algorithm (SPO) and mask region based convolution neural network (mask RCNN). Multimed Tools Appl 81, 31469–31492 (2022). https://doi.org/10.1007/s11042-022-12940-x

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