scholarly journals Cytopathology Using High Resolution Digital Holographic Microscopy

2021 ◽  
Author(s):  
Sarita Ahlawat ◽  
Purnima Sharma ◽  
Ankita Pandey ◽  
Durga Bisht ◽  
Aanisa Jan ◽  
...  
Keyword(s):  
Pap Smear ◽  
Imaging Modality ◽  
Age Groups ◽  
Digital Holographic Microscopy ◽  
Optimization Approach ◽  
Cell Nuclei ◽  
Bright Field ◽  
Quantitative Phase ◽  
Phase Images ◽  
Cervical Cells

We summarize a study involving simultaneous imaging of cervical cells from Pap-smear samples using bright-field and quantitative phase microscopy. The optimization approach to phase reconstruction used in our study enables full diffraction limited performance from single-shot holograms and is thus suitable for reducing cost of a quantitative phase microscope system. Over 48000 cervical cells from patient samples obtained from three clinical sites have been imaged in this study. The clinical sites used different sample preparation methodologies and the subjects represented a range of age groups and geographical diversity. Visual examination of quantitative phase images of cervical cell nuclei show distinct morphological features that we believe have not appeared in the prior literature. A PCA based analysis of numerical parameters derived from the bright-field and quantitative phase images of the cervical cells shows good separation of superficial, intermediate and abnormal cells. The distribution of phase based parameters of normal cells is also shown to be highly overlapping among different patients from the same clinical site, patients across different clinical sites and for two age groups (below and above 30 years), thus suggesting robustness and possibility of standardization of quantitative phase as an imaging modality for cell classification in future clinical usage.

scholarly journals A Hierarchical Feature-Based Methodology to Perform Cervical Cancer Classification

2021 ◽  
Vol 11 (9) ◽  
pp. 4091
Author(s):  
Débora N. Diniz ◽  
Mariana T. Rezende ◽  
Andrea G. C. Bianchi ◽  
Claudia M. Carneiro ◽  
Daniela M. Ushizima ◽  
...  
Keyword(s):  
Cervical Cancer ◽  
Pap Smear ◽  
Hierarchical Classification ◽  
Cell Nuclei ◽  
Test Analysis ◽  
Pap Smear Test ◽  
Microscopy Image ◽  
Feature Based ◽  
Cervical Cells ◽  
Number Of Classes

Prevention of cervical cancer could be performed using Pap smear image analysis. This test screens pre-neoplastic changes in the cervical epithelial cells; accurate screening can reduce deaths caused by the disease. Pap smear test analysis is exhaustive and repetitive work performed visually by a cytopathologist. This article proposes a workload-reducing algorithm for cervical cancer detection based on analysis of cell nuclei features within Pap smear images. We investigate eight traditional machine learning methods to perform a hierarchical classification. We propose a hierarchical classification methodology for computer-aided screening of cell lesions, which can recommend fields of view from the microscopy image based on the nuclei detection of cervical cells. We evaluate the performance of several algorithms against the Herlev and CRIC databases, using a varying number of classes during image classification. Results indicate that the hierarchical classification performed best when using Random Forest as the key classifier, particularly when compared with decision trees, k-NN, and the Ridge methods.

Digital holographic microscopy for phase images of cervical cells 3D structure

2015 ◽  
Author(s):  
M. Mihailescu ◽  
I. A. Paun ◽  
E. I. Scarlat ◽  
I. Grigorescu ◽  
O. T. Nedelcu ◽  
...  
Keyword(s):  
3D Structure ◽  
Digital Holographic Microscopy ◽  
Phase Images ◽  
Holographic Microscopy ◽  
Cervical Cells

scholarly journals Study on Quantitative Phase Imaging by Dual-Wavelength Digital Holography Microscopy

2018 ◽  
Vol 2018 ◽  
pp. 1-8 ◽  
Author(s):  
Lin Hu ◽  
Yunxiu Shui ◽  
Yaohui Dai ◽  
Haiyu Wu ◽  
Gang Zhu ◽  
...  
Keyword(s):  
Phase Distribution ◽  
Dual Wavelength ◽  
Digital Holographic Microscopy ◽  
Phase Imaging ◽  
Quantitative Phase ◽  
Large Gradient ◽  
Phase Images ◽  
Surface Measurements ◽  
Holographic Microscopy ◽  
Error Of Measurement

A dual-wavelength digital holographic microscopy with premagnification is proposed to obtain the object surface measurements over the large gradient. The quantitative phase images of specimens are captured in high precision by the processing of filtering and phase compensation. The phase images are acquired without phase unwrapping, which is necessary in traditional digital holographic microscopy; thereby the proposed system can greatly increase the speed of reconstruction. The results of numerical simulation and optical experiments demonstrated that the reconstructed speed increased by 37.9 times, and the relative error of measurement is 4% compared with the traditional holographic microscopy system. It means that the proposed system can directly acquire the higher quality quantitative phase distribution for specimens.

Sequential processing of quantitative phase images for the study of cell behaviour in real-time digital holographic microscopy

2014 ◽  
Vol 256 (2) ◽  
pp. 117-125 ◽  
Author(s):  
T. ZIKMUND ◽  
L. KVASNICA ◽  
M. TÝČ ◽  
A. KŘÍŽOVÁ ◽  
J. ČOLLÁKOVÁ ◽  
...  
Keyword(s):  
Real Time ◽  
Digital Holographic Microscopy ◽  
Cell Behaviour ◽  
Quantitative Phase ◽  
Sequential Processing ◽  
Phase Images ◽  
Holographic Microscopy

scholarly journals Video-Rate Quantitative Phase Imaging Using a Digital Holographic Microscope and a Generative Adversarial Network

Sensors ◽  
2021 ◽  
Vol 21 (23) ◽  
pp. 8021
Author(s):  
Raul Castaneda ◽  
Carlos Trujillo ◽  
Ana Doblas
Keyword(s):  
Digital Holographic Microscopy ◽  
Reconstruction Method ◽  
Phase Imaging ◽  
Quantitative Phase Imaging ◽  
Generative Adversarial Network ◽  
Experimental Conditions ◽  
Quantitative Phase ◽  
Human Red Blood Cells ◽  
Adversarial Network ◽  
Phase Images

The conventional reconstruction method of off-axis digital holographic microscopy (DHM) relies on computational processing that involves spatial filtering of the sample spectrum and tilt compensation between the interfering waves to accurately reconstruct the phase of a biological sample. Additional computational procedures such as numerical focusing may be needed to reconstruct free-of-distortion quantitative phase images based on the optical configuration of the DHM system. Regardless of the implementation, any DHM computational processing leads to long processing times, hampering the use of DHM for video-rate renderings of dynamic biological processes. In this study, we report on a conditional generative adversarial network (cGAN) for robust and fast quantitative phase imaging in DHM. The reconstructed phase images provided by the GAN model present stable background levels, enhancing the visualization of the specimens for different experimental conditions in which the conventional approach often fails. The proposed learning-based method was trained and validated using human red blood cells recorded on an off-axis Mach–Zehnder DHM system. After proper training, the proposed GAN yields a computationally efficient method, reconstructing DHM images seven times faster than conventional computational approaches.

scholarly journals Transmission Structured Illumination Microscopy for Quantitative Phase and Scattering Imaging

2021 ◽  
Vol 8 ◽  
Author(s):  
Kai Wen ◽  
Ying Ma ◽  
Min Liu ◽  
Jianlang Li ◽  
Zeev Zalevsky ◽  
...  
Keyword(s):  
Imaging Modality ◽  
Ccd Camera ◽  
Fluorescent Labeling ◽  
Fluorescent Imaging ◽  
Structured Illumination ◽  
Structured Illumination Microscopy ◽  
Quantitative Phase ◽  
Phase Images ◽  
Intensity Images ◽  
Fringe Patterns

In this paper, we demonstrate a digital micromirror device (DMD) based optical microscopic apparatus for quantitative differential phase contrast (qDIC) imaging, coherent structured illumination microscopy (SIM), and dual-modality (scattering/fluorescent) imaging. For both the qDIC imaging and the coherent SIM, two sets of fringe patterns with orthogonal orientations and five phase-shifts for each orientation, are generated by a DMD and projected on a sample. A CCD camera records the generated images in a defocusing manner for qDIC and an in-focus manner for coherent SIM. Both quantitative phase images and super-resolved scattering/fluorescence images can be reconstructed from the recorded intensity images. Moreover, fluorescent imaging modality is integrated, providing specific biochemical structures of the sample once using fluorescent labeling.

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