for 2D-MSPC. Finding a solution for this problem can enhance our understanding of the concept of PC and thereby promoting its applications.

Contribution of This Paper
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We have classified the 2D-MSPC optimization problem as follows:

-   What optimization criteria should be used for the tuning of 2D-MSPC parameters?

-   How can we formulate the problem mathematically and compute the parameters of 2D-SMPC optimally and automatically?

This paper aims to address these questions. The 2D-MSPC, its definition, computational method and a list of its fundamental parameters are briefly described in section \[sec:2dmspc\]. The importance of parameter setting in 2D-MSPC IFD, which leads to Q1 and Q2, is discussed in section \[sec:pardisc\]. In section \[sec:opt\], we define a criterion for parameter optimization, based on the maximum and minimum moments of the 2D-MSPC. We formulate the problem in various optimal frameworks, and then describe about a suboptimal solution accordingly. Finally, the effectiveness of the proposed method is verified through several examples from both natural and medical images in section \[sec:ex\]. This includes two examples from magnetic resonance imaging (MRI) of patients with multiple sclerosis (MS). We illustrate that the proposed 2D-MSPC optimization is useful to MS lesions detection.

Nomenclatures
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In this 