MATLAB based Simulation of probe formation and imaging in modern field emission SEMs based on electron wave optics

Demonstrative implementation of a 3D reconstruction and automatic segmentation routine in Python which can be applied to SEM image sequences of particle-like specimens. The image sequences can be acquired by tilting the SEM's stage. More details about the theory underlying are elucidated in Töberg et al.

Nanoscale Microscopy Images Colourisation Using Neural Networks

Graphical user interface that allows for processing and indexing of electron backscatter patterns, generated by scanning electron microscopes.

A flexibility upgrade for multi-channel scanning transmission electron microscopy

Kernel Average Misorientation Analysis of EBSD Patterns

2022 Samsung AI Challenge (3D Metrology) 1st place Solution

Alignment tool for SECM and SEM images

Computer Assisted Segmentation Tool Environment Revisit

Image processing for SEM using machine learning. Adapted from files by https://github.com/bnsreenu/python_for_microscopists

A Java/Processing implementation of the marching cubes algorithm, including normal averaging. A sequence of binary .png files can be provided to show a 3D render of the resulting polygon.

Using deep learning methods to recognize and measure silica spheres in SEM pictures.

Analysis of electron backscatter diffraction (EBSD) patterns of five phases from an Al-steel joint