Optical diffraction tomography with finite object support for the minimization of missing cone artifacts

Area of Science:

• Optics and Photonics
• Image Reconstruction
• Computational Imaging

Background:

• Limited-angle optical diffraction tomography (ODT) is prone to significant artifacts in tomographic reconstructions.
• Existing regularization methods offer improvements but still require enhanced reconstruction quality.

Purpose of the Study:

• To introduce a novel, effective method to improve reconstruction quality in limited-angle ODT.
• To present a technique that complements existing tomographic algorithms.

Main Methods:

• A finite object support is generated directly from the object data.
• This object support is integrated into the reconstruction process as a strong regularization constraint.

Main Results:

• The proposed method significantly reduces artifacts and enhances the quality of tomographic reconstructions.
• Demonstrated practical applicability and effectiveness through various examples.

Conclusions:

• The finite object support regularization is a simple yet powerful addition to limited-angle ODT.
• This approach offers a practical pathway to higher-fidelity tomographic reconstructions in ODT.