You might also read
Articles linked to this work by shared authors, journal, and citation graph.
Updated: Sep 22, 2025

Lens-free Video Microscopy for the Dynamic and Quantitative Analysis of Adherent Cell Culture
Published on: February 23, 2018
Sarinporn Visitsattapongse1, Kitsada Thadson1, Suejit Pechprasarn2
1Department of Biomedical Engineering, School of Engineering, King Mongkut's Institute of Technology Ladkrabang, Bangkok 10520, Thailand.
Deep learning for quantitative phase imaging shows promise but requires careful validation. This study introduces a framework to assess AI-recovered phase images, demonstrating their reliability depends on sample type and input data.
Failed At:
2026-06-19T13:39:34.030435+00:00
14:09Quantitative Optical Microscopy: Measurement of Cellular Biophysical Features with a Standard Optical Microscope
Published on: April 7, 2014
07:38Multimodal Quantitative Phase Imaging with Digital Holographic Microscopy Accurately Assesses Intestinal Inflammation and Epithelial Wound Healing
Published on: September 13, 2016