High-resolution limited-angle phase tomography of dense layered objects using deep neural networks
Abstract
We demonstrate that it is possible to use deep neural networks to produce tomographic reconstructions of dense layered objects with small illumination angle as low as 10 °. It is also shown that a DNN trained on synthetic data can generalize well to and produce reconstructions from experimental measurements. This work has application in the field of X-ray tomography for the inspection of integrated circuits and other materials studies.
Document Details
- Document Type
- Pub Defense Publication
- Publication Date
- Sep 16, 2019
- Source ID
- 10.1073/pnas.1821378116
Entities
People
- Akintunde I. Akinwande
- Alexandre Goy
- George Barbastathis
- Girish Rughoobur
- Kwabena Arthur
- Shuai Li
Organizations
- Intelligence Advanced Research Projects Activity
- Massachusetts Institute of Technology