MRI Noise Index Derivation for Multi-Coil Image Compositing
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Solution Overview
Problem
Current medical image processing technologies face challenges in accurately removing noise from magnetic resonance imaging (MRI) data collected by multiple reception coils, leading to inconsistencies in image quality due to varying noise distributions across images.
Innovation Solution
A medical information processing apparatus and method that derives an index value for noise in MRI data from multiple coils, adjusts the noise removal degree based on this index, and performs denoise processing using a deep neural network model to generate composite images with improved noise reduction while maintaining signal integrity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Object-affected harmful factors
If noise removal processing is applied to MRI data from multiple reception coils, then noise is reduced in the composite image, but image quality becomes inconsistent due to varying noise distributions across different coils
Solution Approach 1:
The patent applies different noise removal processing to each reception coil based on its individual noise distribution characteristics. The processing circuitry derives noise distribution information separately for each coil and adjusts the noise removal degree accordingly, ensuring that each coil's data is optimally processed according to its local noise properties before composite image generation.
Solution Approach 2:
The patent changes the noise removal parameters based on the derived noise distribution information. By adjusting the noise removal degree as a variable parameter according to each coil's specific noise characteristics, the system optimizes the balance between noise reduction and signal preservation for each coil individually.
2Device complexity
If uniform noise removal degree is applied to all reception coils, then processing is simplified, but noise removal accuracy decreases due to varying noise distributions
Solution Approach 1:
The patent performs preliminary derivation of noise distribution information for each reception coil before applying noise removal processing. By obtaining and analyzing the noise characteristics of each coil in advance, the system prepares the necessary parameters for optimized noise removal, ensuring accurate processing without excessive complexity during the main reconstruction phase.
Solution Approach 2:
The patent implements dynamic adjustment of the noise removal degree for each reception coil based on its specific noise distribution. Rather than using a fixed uniform parameter, the system adaptively modifies the noise removal strength according to the actual noise characteristics observed in each coil's data, optimizing the processing for varying conditions.
Data Source
AI summary
According to one embodiment, a medical information processing apparatus includes processing circuitry configured to derive an index value with respect to noise included in data associated with magnetic resonance signals collected by each of a plurality of reception coils, adjust a degree to which noise is removed from the data associated with the magnetic resonance signals based on the derived index value, remove noise from the data associated with the magnetic resonance signals based on the adjusted degree, and perform compositing of the data associated with the magnetic resonance signals from which noise has been removed.