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Search · four archives
27 papers · ranked by Valyu relevance
Mikhail Makarkin, Daniil Bratashov, Aiqun Liu
In modern digital microscopy, deconvolution methods are widely used to eliminate a number of image defects and increase resolution. In this review, we have divided these methods into classical, deep learning-based, and optimization-based methods. The review describes the major architectures of neural networks, such as…
Hayato Ikoma, Michael Broxton, Takamasa Kudo, Gordon Wetzstein
Deconvolution is widely used to improve the contrast and clarity of a 3D focal stack collected using a fluorescence microscope. But despite being extensively studied, deconvolution algorithms can introduce reconstruction artifacts when their underlying noise models or priors are violated, such as when imaging…
Min Guo, Yue Li, Yijun Su, Talley Lambert + 23 more
We describe theoretical and practical advances in algorithm and software design, resulting in ten to several thousand-fold faster deconvolution and multiview fusion than previous methods. First, we adapt methods from medical imaging, showing that an unmatched back projector accelerates Richardson-Lucy deconvolution by…
Martin Welk, Martin Erler
We investigate possibilities to speed up iterative algorithms for nonblind image deconvolution. We focus on algorithms in which convolution with the point-spread function to be deconvolved is used in each iteration, and aim at accelerating these convolution operations as they are typically the most expensive part of…
R. Zanella, G. Zanghirati, R. Cavicchioli, L. Zanni + 3 more
'M. Bertero' 'G. Vicidomini'] Although deconvolution can improve the quality of any type of microscope, the high computational time required has so far limited its massive spreading. Here we demonstrate the ability of the scaled-gradient-projection (SGP) method to provide accelerated versions of the most used…
Haohong Gan, Shiyi Peng, Hailian Hu, Xuan You + 4 more
The resolving power of optical microscopy is fundamentally constrained by the diffraction of light, limiting our ability to visualize subcellular structures. Computational methods, particularly deconvolution, can restore blurred images but critically depend on an accurate point spread function (PSF), whose estimation…
Zachary H. Hendrix, Peter Brown, Tim Flanagan, Douglas P. Shepherd + 2 more
Motivated Bayesian Deconvolution Authors: ['Zachary H. Hendrix' 'Peter Brown' 'Tim Flanagan' 'Douglas P. Shepherd' 'Ayush Saurabh' 'Steve Pressé'] Richardson-Lucy deconvolution is widely used to restore images from degradation caused by the broadening effects of a point spread function and corruption by photon shot…
Jianan Chen, Lydia Y. Liu, Wenchao Han, Dan Wang + 3 more
Advances have been made in the use of deep learning to extract quantitative and predictive information from digital pathology slides, yet many barriers remain before clinical translation and deployment. In particular, models need to be generalizable despite the wide variations in image characteristics due to…
M Laasmaa, M Vendelin, P Peterson
Although confocal microscopes have considerably smaller contribution of out-of-focus light than widefield microscopes, the confocal images can still be enhanced mathematically if the optical and data acquisition effects are accounted for. For that, several deconvolution algorithms have been proposed. As a practical…
Boyoung Kim, Doug Brooks, Alexandra Sorvina, Shane Hickey
To investigate the cellular structure, biomedical researchers often obtain three-dimensional images by combining two-dimensional images taken along the z axis. However, these images are blurry in all directions due to diffraction limitations. This blur becomes more severe when focusing further inside the specimen as…
Martin Welk, Patrik Raudaschl, Thomas Schwarzbauer, Martin Erler + 1 more
'Martin Läuter'] Abstract We investigate efficient algorithmic realisations for robust deconvolution of grey-value images with known space-invariant point-spread function, with emphasis on 1D motion blur scenarios. The goal is to make deconvolution suitable as preprocessing step in automated image processing…
Toby Sanders
Stein's unbiased risk estimator (SURE) has been shown to be an effective metric for determining optimal parameters for many applications. The topic of this article is focused on the use of SURE for determining parameters for blind deconvolution. The parameters include those that define the shape of the point spread…
Yiwei Hou, Wenyi Wang, Yunzhe Fu, Xichuan Ge + 2 more
Despite the grand advances in fluorescence microscopy, the photon budget of fluorescent molecules remains the fundamental limiting factor for major imaging parameters, such as temporal resolution, duration, contrast, and even spatial resolution. Computational methods can strategically utilize the fluorescence photons…
Florin Selaru, Jude M. Phillip, Denis Wirtz, Pei-Hsun Wu
Advancements in computational approaches have enabled robust utilization of histological tissue data. A crucial step in the development of computational tools for the objective and quantitative analysis of tissue sections has been color deconvolution. Color deconvolution functions by separating the absorption of colors…
Joseph Rosen, Simon Alford, Blake Allan, Vijayakumar Anand + 79 more
'Shlomi Arnon' 'Francis Gracy Arockiaraj' 'Jonathan Art' 'Bijie Bai' 'Ganesh M. Balasubramaniam' 'Tobias Birnbaum' 'Nandan S. Bisht' 'David Blinder' 'Liangcai Cao' 'Qian Chen' 'Ziyang Chen' 'Vishesh Dubey' 'Karen Egiazarian' 'Mert Ercan' 'Andrew Forbes' 'G. Gopakumar' 'Yunhui Gao' 'Sylvain Gigan' 'Paweł Gocłowski'…
Wenfeng Tian, Riwang Chen, Liangyi Chen
Super-Resolution: An Odyssey in Harnessing Priors to Enhance Optical Microscopy Resolution Authors: Wenfeng Tian, Riwang Chen, Liangyi Chen The resolution limit defines the SR problem as the recovery of high-frequency components of the true image beyond the cutoff frequency. This process is often referred to as…
Jonathan M. Taylor
Light field microscopy can capture 3D volume datasets in a snapshot, making it a valuable tool for high-speed 3D imaging of dynamic biological events. However, subsequent computational reconstruction of the raw data into a human-interpretable 3D+time image is very time-consuming, limiting the technique’s utility as a…
Marcellin Atemkeng, O. Smirnov, C. Tasse, Griffin Foster + 1 more
'Sphesihle Makhathini'] The desire for wide-field of view, large fractional bandwidth, high sensitivity, high spectral and temporal resolution has driven radio interferometry to the point of big data revolution where the data is represented in at least three dimensions with an axis for spectral windows, baselines…
Adeleke Maradesa, Baptiste Py, Ting Hei Wan, Mohammed B. Effat + 1 more
Electrochemical impedance spectroscopy (EIS) is a characterization technique used widely in electrochemistry. Obtaining EIS data is simple when modern electrochemical workstations are used; however, analyzing EIS spectra is still a considerable quandary. The distribution of relaxation times (DRT) has emerged as a…
Stanley H. Chan
At the pinnacle of computational imaging is the cooptimization of camera and algorithm. This, however, is not the only form of computational imaging. In problems such as imaging through adverse weather, the bigger challenge is how to accurately simulate the forward degradation process so that we can synthesize data to…
Hongyang Dong, Simon D.M. Jacques, Keith T. Butler, Olof Gutowski + 4 more
In this study, we introduce a method designed to eliminate parallax artefacts present in Xray powder diffraction computed tomography data acquired from large samples. These parallax artefacts manifest as artificial peak shifting, broadening and splitting, leading to inaccurate physicochemical information, such as…
Kelsey Hatzell, Yanjie Zheng
X-ray Computed Tomography (CT) is a non-invasive, non-destructive approach to imaging materials, material systems and engineered components in two- and three- dimensions. Acquisition of 3D images requires the collection of hundreds or thousands of through-thickness X-ray radiographic images from different angles. Such…
Hongyang Dong, Simon D.M. Jacques, Winfried Kockelmann, Stephen W. T. Price + 10 more
Hongyang Dong 3 , Simon D.M. Jacques 1 , Winfried Kockelmann 4 , Stephen W. T. Price 1 , Robert Emberson 5 , Dorota Matras 6,7 , Yaroslav Odarchenko 1 , Vesna Middelkoop 10 , Athanasios Giokaris 1 , Olof Gutowski 8 , Ann-Christin Dippel 8 , Martin v. Zimmermann 8 , Andrew M. Beale 3 , Keith T. Butler 9 , Antonis…
Vasily Matkivsky, Alexander Moiseev, Pavel Shilyagin, Alexander Rodionov + 5 more
A method for numerical estimation and correction of aberrations of the eye in fundus imaging with optical coherence tomography (OCT) is presented. Aberrations are determined statistically by using the estimate based on likelihood function maximization. The method can be considered as an extension of the phase gradient…
Authors not listed
nDTomo is a Python-based software suite for the simulation, reconstruction and analysis of X-ray chemical imaging and computed tomography data. It provides a collection of Python function-based tools designed for accessibility and education as well as a graphical user interface (GUI). Prioritising transparency and ease…
Kevin Robben, Christopher Cheatum
We report a comprehensive study of the efficacy of least-squares fitting of multidimensional spectra to generalized Kubo lineshape models and introduce a novel least-squares fitting metric, termed the Scale Invariant Gradient Norm (SIGN), that enables a highly reliable and versatile algorithm. The precision of…
Andrew Harvie, John de Mello
The Open Polarimeter (“Opol”) is a phase-based, high-resolution laser polarimeter formed from a small number of inexpensive optomechanical parts. The complete instrument can be assembled from scratch in two days for less than US$250, using only a 3D-printer and a benchtop milling machine. However despite its low cost…