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Histogram-based normalization technique on human brain magnetic resonance images from different acquisitions
Xiaofei Sun1,2,3, Lin Shi4,5, Yishan Luo1,2
1Department of Imaging and Interventional Radiology, The Chinese University of Hong Kong, Shatin, New Territories, Hong Kong, China.
Biomedical Engineering Online
|July 29, 2015
Summary
This study introduces a novel histogram normalization method to reduce intensity variations in brain MRI scans from different scanners. The new method improves image analysis performance and creates higher quality brain templates.
Area of Science:
- Medical Imaging
- Neuroscience
- Computer Vision
Background:
- Brain magnetic resonance image (MRI) analysis requires intensity normalization due to variations from different scanners and parameters.
- Intensity variations significantly impact MRI processing tasks like registration, segmentation, and tissue volume measurement.
- Standardization is crucial for reliable population-based MRI studies.
Purpose of the Study:
- To develop and validate a new histogram normalization method for reducing intensity variations in brain MRIs acquired across different settings.
- To improve the performance of subsequent MRI analysis tasks through enhanced image standardization.
- To facilitate the creation of higher quality neuroimaging templates.
Main Methods:
- A novel histogram normalization technique was proposed, utilizing a high-quality reference image selected based on noise estimation.
- The method involves two key steps: intensity scaling (IS) and histogram normalization (HN).
- Low-quality MR images are normalized to match the histogram of the high-quality reference image, rescaling intensities within a defined range.
Main Results:
- The proposed histogram normalization method demonstrated superior performance in image registration, segmentation, and tissue volume measurement compared to existing methods.
- Experiments confirmed that preprocessing with the new normalization technique significantly enhances the quality of brain templates.
- The method effectively reduces intensity variations, leading to more accurate downstream analyses.
Conclusions:
- A histogram-based MRI intensity normalization method has been successfully developed and validated.
- The method is capable of normalizing brain MRIs acquired on different MRI units, improving analysis performance.
- This approach enables the creation of higher quality brain templates, particularly beneficial for large-scale studies like the Chinese brain template project.
