13 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…
Paul H. C. Eilers, Cyril Ruckebusch
We present a fast and simple algorithm for super-resolution with single images. It is based on penalized least squares regression and exploits the tensor structure of two-dimensional convolution. A ridge penalty and a difference penalty are combined; the former removes singularities, while the latter eliminates…
Luís M. A. Perdigão, Casper Berger, Neville B.-Y. Yee, Michele C. Darrow + 1 more
The experimental limitations with optics observed in many microscopy and astronomy instruments result in detrimental effects for the imaging of objects. This can be generally described mathematically as a convolution of the real object image with the point spread function that characterizes the optical system. The…
Erik Wernersson, Eleni Gelali, Gabriele Girelli, Su Wang + 13 more
'David Castillo' 'Christoffer Mattsson Langseth' 'Quentin Verron' 'Huy Q. Nguyen' 'Shyamtanu Chattoraj' 'Anna Martinez Casals' 'Hans Blom' 'Emma Lundberg' 'Mats Nilsson' 'Marc A. Marti-Renom' 'Chao-ting Wu' 'Nicola Crosetto' 'Magda Bienko'] Microscopy-based spatially resolved omic methods are transforming the life…
Amit Kohli, Anastasios N. Angelopoulos, David McAllister, Esther Whang + 6 more
'Esther Whang' 'Sixian You' 'Kyrollos Yanny' 'Federico M. Gasparoli' 'Bo-Jui Chang' 'Reto Fiolka' 'Laura Waller'] The most ubiquitous form of aberration correction for microscopy is deconvolution; however, deconvolution relies on the assumption that the system’s point spread function is the same across the entire field…
Yuchen Xiang, Martin Metodiev, Meiqi Wang, Boxuan Cao + 3 more
'Josephine Bunch' 'Zoltan Takats' 'Olimpio Montero'] Mass spectrometry imaging (MSI) has been a key driver of groundbreaking discoveries in a number of fields since its inception more than 50 years ago. Recently, MSI development trends have shifted towards ambient MSI (AMSI) as the removal of sample-preparation steps…
Yiming Liu, Sjoerd Stallinga
The gradient-consensus Richardson-Lucy (GC-RL) deconvolution algorithm is a novel approach to contrast restoration in high-resolution microscopy imaging without excessive noise amplification. We evaluate this method in this work, focusing on the impact of the noise level of the input image, of imperfections and…
Philip Wijesinghe, Stella Corsetti, Darren J. X. Chow, Shuzo Sakata + 2 more
'Kylie R. Dunning' 'Kishan Dholakia'] Deconvolution is a challenging inverse problem, particularly in techniques that employ complex engineered point-spread functions, such as microscopy with propagation-invariant beams. Here, we present a deep-learning method for deconvolution that, in lieu of end-to-end training with…
Francisco J. Ávila, Juan M. Bueno, Raimondo Schettini
The optical quality of an image depends on both the optical properties of the imaging system and the physical properties of the medium the light passes while travelling from the object to the image plane. The computation of the point spread function (PSF) associated to the optical system is often used to assess the…
Alexander Sachuk, Ekaterina Volkova, Anastasiya Rakovskaya, Vyacheslav Chukanov + 2 more
Fluorescence microscopy performance can be significantly enhanced with image post-processing algorithms, particularly deconvolution techniques. These methods aim to revert optical aberrations by deconvolving the image with the point spread function (PSF) of the microscope. However, analytical deconvolution algorithms…
Michael Slutsky, Markus Lienkamp, Maximilian Geisslinger, Felix Fent + 1 more
'Zhengguo Li'] This work addresses the problem of non-blind image deblurring for arbitrary input noise. The problem arises in the context of sensors with strong chromatic aberrations, as well as in standard cameras, in low-light and high-speed scenarios. A short description of two common classical approaches to…
Min Guo, Yicong Wu, Chad M. Hobson, Yijun Su + 22 more
'Eric Krueger' 'Ryan Christensen' 'Grant Kroeschell' 'Johnny Bui' 'Matthew Chaw' 'Lixia Zhang' 'Jiamin Liu' 'Xuekai Hou' 'Xiaofei Han' 'Zhiye Lu' 'Xuefei Ma' 'Alexander Zhovmer' 'Christian Combs' 'Mark Moyle' 'Eviatar Yemini' 'Huafeng Liu' 'Zhiyi Liu' 'Alexandre Benedetto' 'Patrick La Riviere' 'Daniel Colón-Ramos'…
Emmanouil Xypakis, Giorgio Gosti, Taira Giordani, Raffaele Santagati + 2 more
'Giancarlo Ruocco' 'Marco Leonetti'] Blind-structured illumination microscopy (blind-SIM) enhances the optical resolution without the requirement of nonlinear effects or pre-defined illumination patterns. It is thus advantageous in experimental conditions where toxicity or biological fluctuations are an issue. In this…