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AAPM Truth-based CT (TrueCT) reconstruction grand challenge.

Ehsan Abadi^1,2,3, W Paul Segars^1,2,4, Nicholas Felice^1,2

¹Center for Virtual Imaging Trial, Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University School of Medicine, Durham, North Carolina, USA.

Medical Physics

|January 14, 2025

Summary

This summary is machine-generated.

The 2022 AAPM grand challenge used virtual imaging to objectively assess CT reconstruction methods. Participant "A" showed the best overall performance across emphysema, lung, and liver lesion models.

Keywords:

AAPM grand challenge CT reconstruction computational phantoms computed tomography imaging simulators in silico trials medical imaging simulations virtual imaging trials

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Area of Science:

Medical Imaging
Computational Modeling
Radiology

Background:

The 2022 AAPM grand challenge focused on truth-based computed tomography (CT) image reconstruction.
This report details the challenge's methodology and findings.

Purpose of the Study:

To establish an objective framework for evaluating CT reconstruction techniques.
Utilized a virtual imaging resource with simulated CT projection images of diverse human models with diseases.

Main Methods:

Created 200 computational human models with emphysema, lung lesions, and liver lesions based on clinical CT data.
Simulated CT imaging, shared sinograms with participants for image reconstruction, and scored results against ground truth.
Employed task-generic (RMSE, SSIM) and task-specific (d', lesion volume accuracy) metrics for evaluation.

Main Results:

52 participants initially, with 5 completing the challenge, submitting 200 reconstructions.
Participant "A" achieved the best overall performance across disease types, demonstrating the effectiveness of their reconstruction method.
Performance metrics varied, with SSIM ranging from 0.22 to 0.90 and RMSE from 77.6 to 490.5 HU.

Conclusions:

The True-CT challenge successfully provided an objective assessment of CT reconstructions using virtual diseased human models.
Virtual imaging trials hold significant potential for the objective evaluation of medical imaging technologies.