Optical diffraction tomography with finite object support for the minimization of missing cone artifacts
Wojciech Krauze
Abstract
Limited-angle optical diffraction tomography suffers from strong artifacts in tomographic reconstructions. Numerous algorithms, mainly based on regularization methods, have been developed recently to overcome this limitation. However, the quality of results still needs further improvement. Here I present a simple yet extremely effective method of increasing the reconstruction quality in limited angle optical diffraction tomography that can be combined with known tomographic algorithms. In the method a finite object support is generated from the object data and utilized in the reconstruction procedure as an additional strong regularizer. Practical aspects of this method are given together with examples of application.
Topics & Concepts
TomographyTomographic reconstructionComputer scienceDiffraction tomographyIterative reconstructionRegularization (linguistics)Diffuse optical imagingDiffractionOpticsImage qualityObject (grammar)Computer visionAlgorithmArtificial intelligenceImage (mathematics)PhysicsDigital Holography and MicroscopyMedical Imaging Techniques and ApplicationsPhotoacoustic and Ultrasonic Imaging