Image quality evaluation for FIB-SEM images.
Diego RoldánClaudia RedenbachKatja SchladitzChristian KübelSabine SchlabachPublished in: Journal of microscopy (2023)
FIB-SEM tomography is a serial sectioning technique where a Focused Ion Beam (FIB) mills off slices from the material sample that is being analyzed. After every slicing, a Scanning Electron Microscopy (SEM) image is taken showing the newly exposed layer of the sample. By combining all slices in a stack, a 3D image of the material is generated. However, specific artifacts caused by the imaging technique distort the images, hampering the morphological analysis of the structure. Typical quality problems in microscopy imaging are noise and lack of contrast or focus. Moreover, specific artifacts are caused by the FIB milling, namely, curtaining and charging artifacts. We propose quality indexes for the evaluation of the quality of FIB-SEM data sets. The indexes are validated on real and experimental data of different structures and materials. This article is protected by copyright. All rights reserved.
Keyphrases
- image quality
- electron microscopy
- high resolution
- deep learning
- liver fibrosis
- computed tomography
- optical coherence tomography
- convolutional neural network
- electronic health record
- quality improvement
- big data
- mental health
- dual energy
- air pollution
- mass spectrometry
- machine learning
- magnetic resonance imaging
- single cell