The fMRI Study of Creative Thinking in Art Design

Abstract

Magnetic resonance imaging (MRI) has rich contrast information, high resolution, can be sliced in any direction, and has no radiation damage, which plays an important role in clinical diagnosis. The research on the brain mechanism of human creative thinking is one of the hot spots, and it has always attracted the attention of various fields. Intelligent Computer Aided Design (The multi-source analogy generation model in is a quantifiable model, which simulates the process of creative thinking to a certain extent. First, four common parallel MRI image reconstruction algorithms SENSE, SMASH, GRAPPA and PILS are deeply studied in this paper, and the impact of different reconstruction algorithms and different acceleration factor combinations on the quality of reconstructed images is analyzed. The experimental results show that: neural network recognition through feature level fusion The ability of benign and malignant prostate tumors is improved by at least 10%. This feature level fusion strategy is effective and improves the irrelevance between features to a certain extent.