title: Automated Fourier space region-recognition filtering for off-axis digital holographic microscopy.
abstract: Automated label-free quantitative imaging of biological samples can greatly benefit high throughput diseases diagnosis. Digital holographic microscopy (DHM) is a powerful quantitative label-free imaging tool that retrieves structural details of cellular samples non-invasively. In off-axis DHM, a proper spatial filtering window in Fourier space is crucial to the quality of reconstructed phase image. Here we describe a region-recognition approach that combines shape recognition with an iterative thresholding method to extracts the optimal shape of frequency components. The region recognition technique offers fully automated adaptive filtering that can operate with a variety of samples and imaging conditions. When imaging through optically scattering biological hydrogel matrix, the technique surpasses previous histogram thresholding techniques without requiring any manual intervention. Finally, we automate the extraction of the statistical difference of optical height between malaria parasite infected and uninfected red blood cells. The method described here paves way to greater autonomy in automated DHM imaging for imaging live cell in thick cell cultures.
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia.
authors: Xuefei
authors: X
authors: He
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia; ARC Centre of Excellence for Robotics Vision, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia.
authors: Chuong Vinh
authors: CV
authors: Nguyen
authors: Research School of Biology, College of Medicine, Biology and Environment, The Australian National University, Canberra ACT 2601, Australia.
authors: Mrinalini
authors: M
authors: Pratap
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia.
authors: Yujie
authors: Y
authors: Zheng
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia.
authors: Yi
authors: Y
authors: Wang
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia.
authors: David R
authors: DR
authors: Nisbet
authors: School of Aerospace, Mechanical and Manufacturing Engineering and the Health Innovations Research Institute, RMIT University, Melbourne, Australia.
authors: Richard J
authors: RJ
authors: Williams
authors: Centre for Advanced Microscopy, ANU College of Physical & Mathematical Sciences, The Australian National University, Canberra, ACT 2601, Australia.
authors: Melanie
authors: M
authors: Rug
authors: Research School of Biology, College of Medicine, Biology and Environment, The Australian National University, Canberra ACT 2601, Australia.
authors: Alexander G
authors: AG
authors: Maier
authors: Research School of Engineering, College of Engineering and Computer Science, The Australian National University, Canberra ACT 2601, Australia; Australia Research Council Centre of Excellence in Advanced Molecular Imaging, Australia; steve.lee@anu.edu.au.
authors: Woei Ming
authors: WM
authors: Lee
keywords: (070.0070) Fourier optics and signal processing; (090.0090) Holography; (100.0100) Image processing; (180.0180) Microscopy