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Acquisition of High-Quality Digital Video of Drosophila Larval and Adult Behaviors from a Lateral Perspective

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Digital breast tomosynthesis: Image acquisition principles and artifacts.

Parvinder S Sujlana¹, Mahadevappa Mahesh¹, Srinivasan Vedantham²

¹Johns Hopkins Medical Institutions, The Russell H. Morgan Department of Radiology and Radiological Science, 601 N. Wolfe Street, Baltimore, MD 21287, United States of America.

Clinical Imaging

|September 22, 2018

Summary

This summary is machine-generated.

Digital breast tomosynthesis (DBT) offers 3D imaging for improved cancer detection. Understanding DBT artifacts is crucial for accurate diagnosis and reducing false positives in breast cancer screening.

Keywords:

Artifacts Digital breast tomosynthesis Physics Synthesized mammograms

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Area of Science:

Medical Imaging
Radiology
Biophysics

Background:

Digital breast tomosynthesis (DBT) is increasingly used for breast cancer screening and diagnosis.
DBT provides a 3D dataset, enhancing diagnostic accuracy by distinguishing lesions from tissue overlap compared to 2D mammography.
Synthesized mammograms (SM) from DBT data reduce radiation dose by eliminating the need for separate 2D FFDM acquisition.

Purpose of the Study:

To review the physics principles underlying DBT systems.
To explain the origin of artifacts in DBT and SM imaging.
To aid radiologists in artifact identification and reduction, improving diagnostic evaluation.

Main Methods:

Review of physics principles of DBT systems.
Analysis of how limited angular range and prolonged imaging contribute to artifacts.
Explanation of artifact etiology based on DBT system mechanics and reconstruction algorithms.

Main Results:

DBT systems utilize a movable X-ray tube and reconstruction algorithms to create 3D datasets.
Artifacts in DBT and SM are often caused by incomplete sampling due to limited angular range and prolonged imaging time.
Understanding artifact origins is key to differentiating true findings from imaging artifacts.

Conclusions:

DBT technology offers significant advantages in breast cancer detection.
Artifacts are an inherent challenge in DBT and SM imaging.
Knowledge of artifact etiology can decrease recall and false positive rates, enhancing diagnostic confidence.