Real-time axial motion detection and correction for single photon emission computed tomography using a linear...

Area of Science:

• Medical Imaging
• Nuclear Medicine
• Image Processing

Background:

• Patient motion during SPECT scans introduces artifacts, compromising image quality and diagnostic accuracy.
• Real-time motion detection and correction are crucial for reliable SPECT imaging.

Purpose of the Study:

• To develop and validate a novel algorithm for real-time detection and correction of patient motion during SPECT.
• To implement a linear prediction filter (LPC)-based approach for motion artifact mitigation.

Main Methods:

• The prediction of projection data algorithm (PPDA) compares predicted and measured frame data to detect motion.
• If motion is detected, scanning is paused, and rescanning is performed for corrupted frames.
• The PPDA evaluates data accuracy after each frame acquisition.

Main Results:

• The PPDA demonstrated effective detection of various patient motions (head, legs, hands).
• Validation with approximately 100 test cases showed promising results for the motion detection algorithm.
• The algorithm successfully prevented the collection of motion-corrupted data.

Conclusions:

• The PPDA enables real-time correction of patient motion effects in SPECT imaging.
• By replacing corrupted frames with motion-free data through rescanning, diagnostic quality is enhanced.
• This method significantly improves the reliability of SPECT scans by mitigating motion artifacts.