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Calibration Curves: Correlation Coefficient

Calibration Curves: Correlation Coefficient

In a linear calibration curve, there is a value called the calibration coefficient, denoted by 'r,' which measures the strength and the direction of association between two variables. The correlation coefficient value ranges from −1 to +1. A value of +1 indicates a perfect positive linear correlation, −1 denotes a perfect negative correlation, and 0 implies no correlation between the two variables. A positive correlation value establishes that as one variable increases, the other increases, and...

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Updated: May 11, 2026

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function

Continuous Blood Sampling in Small Animal Positron Emission Tomography/Computed Tomography Enables the Measurement of the Arterial Input Function

Published on: August 8, 2019

TOF PET offset calibration from clinical data.

M E Werner¹, J S Karp

¹Department of Radiology, The University of Pennsylvania, Philadelphia, PA 19104, USA. matt.werner@uphs.upenn.edu

Physics in Medicine and Biology

|May 21, 2013

Summary

This summary is machine-generated.

This study introduces automated timing calibration for time-of-flight positron emission tomography (TOF PET) using existing data. This method enhances TOF PET imaging without specialized equipment, improving image quality and accessibility.

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Area of Science:

Medical Imaging
Nuclear Medicine
Positron Emission Tomography

Background:

Accurate timing calibration is crucial for Time-of-Flight Positron Emission Tomography (TOF PET) image reconstruction.
Existing calibration methods often require specialized data acquisition protocols, limiting their flexibility and automation.

Purpose of the Study:

To present a novel, automated timing calibration technique for TOF PET.
To eliminate the need for dedicated calibration scans, enabling calibration using any clinical dataset.

Main Methods:

Developed a calibration method that integrates directly into the reconstruction process.
The technique utilizes arbitrary TOF PET datasets for calibration, allowing for retroactive application and use with existing data.

Main Results:

The proposed method provides fully automated timing calibration for TOF PET.
It can be applied to any clinical dataset, even retrospectively, without specialized acquisition.
Performance comparison demonstrates competitive results against existing calibration techniques.

Conclusions:

This automated calibration technique significantly improves the practicality and accessibility of TOF PET imaging.
It allows for improved image quality and correction of suboptimal or missing calibrations in retrospective datasets.