PROCESSING AND VISUALIZATION OF LIGHT MICROSCOPE IMAGES

2009 ◽  
Vol 09 (03) ◽  
pp. 369-388
Author(s):  
MAURICIO RAFAEL MAURER ◽  
HELIO PEDRINI ◽  
MARCO ANTONIO FERREIRA RANDI
Keyword(s):  
Image Analysis ◽  
Magnetic Resonance ◽  
Three Dimensional ◽  
Real Data ◽  
Data Sets ◽  
Complex Structures ◽  
X Ray ◽  
Knowledge Domains ◽  
Microscope Images ◽  
Effective Transfer

The analysis of three-dimensional structures of tissues and cellular constituents is a fundamental task in Biology and Medicine. Although three-dimensional images, acquired by light microscopes, play an important role in such knowledge domains, their analysis has not been much exploited compared to other imaging technologies, such as X-ray radiography, computerized tomography or magnetic resonance. In light microscopy, the majority of the activities involved in the image analysis (for instance, detection, counting, quantification) is still performed manually. The main difficulties among the others include the fact that the objects under investigation usually have complex structures, large number of cellular elements, shape variations and presence of noise in the acquired images. This paper describes a method for processing and visualization of images obtained with light microscopes. An effective transfer function based on the optical density of the cellular constituents is employed to generate the volumetric visualization. Several real data sets are used to demonstrate the effectiveness of the proposed method.

scholarly journals Simultaneous Robot–World and Hand–Eye Calibration without a Calibration Object

Sensors ◽  
2018 ◽  
Vol 18 (11) ◽  
pp. 3949 ◽  
Author(s):  
Wei Li ◽  
Mingli Dong ◽  
Naiguang Lu ◽  
Xiaoping Lou ◽  
Peng Sun
Keyword(s):  
Three Dimensional ◽  
Real Data ◽  
Medical Robotics ◽  
Calibration Method ◽  
Bundle Adjustment ◽  
Data Sets ◽  
Rigid Transformation ◽  
Validation Experiment ◽  
Dimensional Reconstruction ◽  
Sparse Bundle Adjustment

An extended robot–world and hand–eye calibration method is proposed in this paper to evaluate the transformation relationship between the camera and robot device. This approach could be performed for mobile or medical robotics applications, where precise, expensive, or unsterile calibration objects, or enough movement space, cannot be made available at the work site. Firstly, a mathematical model is established to formulate the robot-gripper-to-camera rigid transformation and robot-base-to-world rigid transformation using the Kronecker product. Subsequently, a sparse bundle adjustment is introduced for the optimization of robot–world and hand–eye calibration, as well as reconstruction results. Finally, a validation experiment including two kinds of real data sets is designed to demonstrate the effectiveness and accuracy of the proposed approach. The translation relative error of rigid transformation is less than 8/10,000 by a Denso robot in a movement range of 1.3 m × 1.3 m × 1.2 m. The distance measurement mean error after three-dimensional reconstruction is 0.13 mm.

scholarly journals A Note on the Properties of Generalised Separable Spatial Autoregressive Process

2009 ◽  
Vol 2009 ◽  
pp. 1-11 ◽  
Author(s):  
Mahendran Shitan ◽  
Shelton Peiris
Keyword(s):  
Three Dimensional ◽  
Real Data ◽  
Autoregressive Process ◽  
Spatial Modelling ◽  
Spectral Density Function ◽  
Data Sets ◽  
Additional Parameter ◽  
New Class ◽  
Spatial Autoregressive ◽  
Modelling And Forecasting

Spatial modelling has its applications in many fields like geology, agriculture, meteorology, geography, and so forth. In time series a class of models known as Generalised Autoregressive (GAR) has been introduced by Peiris (2003) that includes an index parameterδ. It has been shown that the inclusion of this additional parameter aids in modelling and forecasting many real data sets. This paper studies the properties of a new class of spatial autoregressive process of order 1 with an index. We will call this aGeneralised Separable Spatial Autoregressive(GENSSAR) Model. The spectral density function (SDF), the autocovariance function (ACVF), and the autocorrelation function (ACF) are derived. The theoretical ACF and SDF plots are presented as three-dimensional figures.

scholarly journals Determination of crystallographic intensities from sparse data

IUCrJ ◽  
2015 ◽  
Vol 2 (1) ◽  
pp. 29-34 ◽  
Author(s):  
Kartik Ayyer ◽  
Hugh T. Philipp ◽  
Mark W. Tate ◽  
Jennifer L. Wierman ◽  
Veit Elser ◽  
...  
Keyword(s):  
Diffraction Data ◽  
Crystal Size ◽  
Three Dimensional ◽  
Sparse Data ◽  
Data Sets ◽  
X Rays ◽  
Diffraction Intensity ◽  
X Ray ◽  
Proof Of Principle

X-ray serial microcrystallography involves the collection and merging of frames of diffraction data from randomly oriented protein microcrystals. The number of diffracted X-rays in each frame is limited by radiation damage, and this number decreases with crystal size. The data in the frame are said to be sparse if too few X-rays are collected to determine the orientation of the microcrystal. It is commonly assumed that sparse crystal diffraction frames cannot be merged, thereby setting a lower limit to the size of microcrystals that may be merged with a given source fluence. TheEMCalgorithm [Loh & Elser (2009),Phys. Rev. E,80, 026705] has previously been applied to reconstruct structures from sparse noncrystalline data of objects with unknown orientations [Philippet al.(2012),Opt. Express,20, 13129–13137; Ayyeret al.(2014),Opt. Express,22, 2403–2413]. Here, it is shown that sparse data which cannot be oriented on a per-frame basis can be used effectively as crystallographic data. As a proof-of-principle, reconstruction of the three-dimensional diffraction intensity using sparse data frames from a 1.35 kDa molecule crystal is demonstrated. The results suggest that serial microcrystallography is, in principle, not limited by the fluence of the X-ray source, and collection of complete data sets should be feasible at, for instance, storage-ring X-ray sources.

Three-dimensional Visualization of Neurovascular Compression: Presurgical Use of Virtual Endoscopy Created from Magnetic Resonance Imaging

2008 ◽  
Vol 63 (suppl_1) ◽  
pp. ONS139-ONS146 ◽  
Author(s):  
Tetsuro Takao ◽  
Makoto Oishi ◽  
Masafumi Fukuda ◽  
Go Ishida ◽  
Mitsuya Sato ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Trigeminal Neuralgia ◽  
Three Dimensional ◽  
Virtual Endoscopy ◽  
Surgical Approaches ◽  
Data Sets ◽  
Neurovascular Compression ◽  
Magnetic Resonance Data ◽  
Resonance Data ◽  
Neurovascular Structures

Abstract Objective: To assess the usefulness of presurgical simulation of microvascular decompression (MVD) by virtual endoscopy (VE), a new tool to analyze three-dimensionally reconstructed magnetic resonance data sets in patients with trigeminal neuralgia or hemifacial spasm (HFS). Methods: In 17 patients (10 with trigeminal neuralgia and seven with HFS) determined to be candidates for MVD, we performed presurgical simulation of MVD using VE. We used constructive interference in steady-state imaging and magnetic resonance angiography to obtain the original images. VE findings were compared with surgical findings. Results: The three-dimensional relations between visible structures seen on VE were consistent with intraoperative findings in all patients. In total, 20 (91%) of 22 neurovascular compression sites in all 17 patients were correctly delineated on VE, with the exception of two small branches identified as offending vessel in two patients with HFS. Perforators that were not apparent on VE limited our ability to accomplish transpositioning of the offending vessels as simulated. The positions of structures that can affect individual surgical approaches, such as the petrosal vein, cerebellar flocculus, and vertebral artery, were also adequately predicted on VE. All patients had excellent surgical outcomes. Conclusion: Presurgical VE in patients with trigeminal neuralgia or HFS is a novel technique that provides excellent visualization of the three-dimensional relations between neurovascular structures and allows simulation of MVD.

Noninvasive Magnetic Resonance to Three-Dimensional Rotational X-Ray Registration of Vertebral Bodies for Image-Guided Spine Surgery

Spine ◽  
2004 ◽  
Vol 29 (3) ◽  
pp. 293-297 ◽  
Author(s):  
Everine B. van de Kraats ◽  
Theo van Walsum ◽  
Jorrit-Jan Verlaan ◽  
F. Cumhur Öner ◽  
Max A. Viergever ◽  
...  
Keyword(s):  
Magnetic Resonance ◽  
Spine Surgery ◽  
Three Dimensional ◽  
X Ray ◽  
Image Guided ◽  
Vertebral Bodies

X-ray diffraction contrast tomography: a novel technique for three-dimensional grain mapping of polycrystals. II. The combined case

2008 ◽  
Vol 41 (2) ◽  
pp. 310-318 ◽  
Author(s):  
Greg Johnson ◽  
Andrew King ◽  
Marcelo Goncalves Honnicke ◽  
J. Marrow ◽  
Wolfgang Ludwig
Keyword(s):  
Electron Backscatter Diffraction ◽  
Three Dimensional ◽  
Real Data ◽  
X Ray Diffraction ◽  
Data Set ◽  
Transmitted Beam ◽  
X Ray ◽  
Diffraction Contrast ◽  
Simultaneous Acquisition ◽  
Backscatter Diffraction

By simultaneous acquisition of the transmitted and the diffracted beams, the applicability of the previously introduced diffraction contrast tomography technique [Ludwig, Schmidt, Lauridsen & Poulsen (2008).J. Appl. Cryst.41, 302–309] can be extended to the case of undeformed polycrystalline samples containing more than 100 grains per cross section. The grains are still imaged using the occasionally occurring diffraction contribution to the X-ray attenuation coefficient, which can be observed as a reduction in the intensity of the transmitted beam when a grain fulfils the diffraction condition. Automating the segmentation of the extinction spot images is possible with the additional diffracted beam information, even in the presence of significant spot overlap. By pairing the corresponding direct (`extinction') and diffracted beam spots a robust sorting and indexing approach has been implemented. The analysis procedure is illustrated on a real data set and the result is validated by comparison with a two-dimensional grain map obtained by electron backscatter diffraction.

scholarly journals Characterization of peptide-protein relationships in protein ambiguity groups via bipartite graphs

2021 ◽  
Author(s):  
Karin Schork ◽  
Michael Turewicz ◽  
Julian Uszkoreit ◽  
Jörg Rahnenführer ◽  
Martin Eisenacher
Keyword(s):  
Real Data ◽  
Bipartite Graphs ◽  
Data Sets ◽  
Complex Structures ◽  
Protein Databases ◽  
Protein Inference ◽  
The Relationship ◽  
Ambiguity Groups ◽  
Proteins And Peptides

Motivation: In bottom-up proteomics, proteins are enzymatically digested before measurement with mass spectrometry. The relationship between proteins and peptides can be represented by bipartite graphs. This representation is useful to aid protein inference and quantification, which is complex due to the occurrence of shared peptides. We conducted a comprehensive analysis of bipartite graphs using theoretical peptides from in silico digestion of protein databases as well as quantified peptides quantified from real data sets. Results: The graphs based on quantified peptides are smaller and have less complex structures compared to graphs using theoretical peptides. The proportion of protein nodes without unique peptides and of graphs that contain such proteins are considerably greater for real data. Large differences between the two analyzed organisms (mouse and yeast) on database as well as quantitative level have been observed. Insights of this analysis may be useful for the development of protein inference and quantification algorithms.

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