2023 · IEEE SIU 2023

A Transformer-Based Real-Time Focus Detection Technique for Wide-Field Interferometric Microscopy

Can Polat , Alper Güngör , Mustafa Yorulmaz , Bilal Kızılelma , Tolga Çukur

TL;DR

A transformer-based focus-detection method for wide-field interferometric microscopy, fast enough to run in the imaging loop instead of offline.

Abstract

Wide-field interferometric microscopy (WIM) has been utilized for visualization of individual biological nanoparticles with high sensitivity. However, the image quality is highly affected by the focusing of the image. Hence, focus detection has been an active research field within the scope of imaging and microscopy. To tackle this issue, we propose a novel convolution and transformer based deep learning technique to detect focus in WIM. The method is compared to other focus detecton techniques and is able to obtain higher precision with less number of parameters. Furthermore, the model achieves real-time focus detection thanks to its low inference time.

Cite

@article{polat2023transformerbased,
  title = {A Transformer-Based Real-Time Focus Detection Technique for Wide-Field Interferometric Microscopy},
  author = {Can Polat and Alper Güngör and Mustafa Yorulmaz and Bilal Kızılelma and Tolga Çukur},
  year = 2023,
  journal = {IEEE SIU 2023},
  doi = {10.1109/siu59756.2023.10223991},
}