R
Renata Rychtáriková
Researcher at Sewanee: The University of the South
Publications - 45
Citations - 162
Renata Rychtáriková is an academic researcher from Sewanee: The University of the South. The author has contributed to research in topics: Rényi entropy & Microscopy. The author has an hindex of 7, co-authored 44 publications receiving 153 citations. Previous affiliations of Renata Rychtáriková include Academy of Sciences of the Czech Republic & University of South Bohemia in České Budějovice.
Papers
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Journal ArticleDOI
Super-resolved 3-D imaging of live cells’ organelles from bright-field photon transmission micrographs
Renata Rychtáriková,Tomáš Náhlík,Kevin Shi,Daria Malakhova,Petr Macháček,Rebecca W. Smaha,Jan Urban,Dalibor Štys +7 more
TL;DR: An algorithm for complete 3-D modelling of cellular structures from a z-stack of images obtained using label-free wide-field bright-field light-transmitted microscopy, where the detection limit of objects is only limited by the technical specifications of the microscope setup.
Journal ArticleDOI
Point Information Gain and Multidimensional Data Analysis
Renata Rychtáriková,Jan Korbel,Petr Macháček,Petr Císař,Jan Urban,Dmytro Soloviov,Dalibor Štys +6 more
TL;DR: The main properties of PIE/PIED spectra for the real data with the examples of several images are demonstrated and further possible utilizations in other fields of data processing are discussed.
Book ChapterDOI
Least Information Loss (LIL) Conversion of Digital Images and Lessons Learned for Scientific Image Inspection
TL;DR: The main aim of this article is introducing least information loss (LIL) algorithm as a novel approach to minimize the information loss caused by the transformation the primary camera signals to 8 bit per pixel.
Book ChapterDOI
Multifractality in Imaging: Application of Information Entropy for Observation of Inner Dynamics Inside of an Unlabeled Living Cell in Bright-Field Microscopy
Renata Rychtáriková,Tomáš Náhlík,Rebecca W. Smaha,Jan Urban,Dalibor StysJr.,Petr Cisar,Dalibor Štys +6 more
TL;DR: The determination of image features based on a general assumption that images transmitted by an optical microscope have multifractal character is presented, and a Point Divergence Gain variable is derived from the Renyi entropy to identify the border of the point spread function of immovable identifiable objects.
Journal ArticleDOI
Point Information Gain and Multidimensional Data Analysis
TL;DR: In this article, the authors generalize the point information gain (PIG) and derived quantities, i.e., Point Information Gain Entropy (PIE) and Point Information gain Entropy Density (PIED), for the case of the Renyi entropy and simulate the behavior of PIG for typical distributions.