Multiscale optical flow computation from the monogenic signal

We have developed an algorithm for the estimation of cardiac motion from medical images. The algorithm exploits monogenic signal theory, recently introduced as an N-dimensional generalization of the analytic signal. The displacement is computed locally by assuming the conservation of the monogenic phase over time. A local affine displacement model replaces the standard translation model to account for more complex motions as contraction/expansion and shear. A coarse-to-fine B-spline scheme allows a robust and effective computation of the models parameters and a pyramidal refinement scheme helps handle large motions. Robustness against noise is increased by replacing the standard pointwise computation of the monogenic orientation with a more robust least-squares orientation estimate. This paper reviews the results obtained on simulated cardiac images from different modalities, namely 2D and 3D cardiac ultrasound and tagged magnetic resonance. We also show how the proposed algorithm represents a valuable alternative to state-of-the-art algorithms in the respective fields.     

Geometry of the superior colliculus mapping and efficient oculomotor computation

Numerous brain regions encode variables using spatial distribution of activity in neuronal maps. Their specific geometry is usually explained by sensory considerations only. We provide here, for the first time, a theory involving the motor function of the superior colliculus to explain the geometry of its maps. We use six hypotheses in accordance with neurobiology to show that linear and logarithmic mappings are the only ones compatible with the generation of saccadic motor command. This mathematical proof gives a global coherence to the neurobiological studies on which it is based. Moreover, a new solution to the problem of saccades involving both colliculi is proposed. Comparative simulations show that it is more precise than the classical one.     

Visual computation and saccadic eye movements: a theoretical perspective

A simple instance of parallel computation in neural networks occurs when the eye orients to a novel visual target. Consideration of target-elicited saccadic eye movements opens the question of how spatial position is represented in the visual pathways involved in this response. It is argued that a point-for-point retinotopic coding of spatial position (the 'local sign' approach) is inadequate to account for the characteristics of the response. An alternative approach based on distributed coding is developed.     

Optimization of flow cytometric detection and cell sorting of transgenic Plasmodium parasites using interchangeable optical filters

ABSTRACT: BACKGROUND: Malaria remains a major cause of morbidity and mortality worldwide. Flow cytometry-based assays that take advantage of fluorescent protein (FP)-expressing malaria parasites have proven to be valuable tools for quantification and sorting of specific subpopulations of parasite-infected red blood cells. However, identification of rare subpopulations of parasites using green fluorescent protein (GFP) labelling is complicated by autofluorescence (AF) of red blood cells and low signal from transgenic parasites. It has been suggested that cell sorting yield could be improved by using filters that precisely match the emission spectrum of GFP. METHODS: Detection of transgenic Plasmodium falciparum parasites expressing either tdTomato or GFP was performed using a flow cytometer with interchangeable optical filters. Parasitaemia was evaluated using different optical filters and, after optimization of optics, the GFP-expressing parasites were sorted and analysed by microscopy after cytospin preparation and by imaging cytometry. RESULTS: A new approach to evaluate filter performance in flow cytometry using two-dimensional dot blot was developed. By selecting optical filters with narrow bandpass (BP) and maximum position of filter emission close to GFP maximum emission in the FL1 channel (510/20, 512/20 and 517/20; dichroics 502LP and 466LP), AF was markedly decreased and signalbackground improve dramatically. Sorting of GFP-expressing parasite populations in infected red blood cells at 90 or 95% purity with these filters resulted in 50-150% increased yield when compared to the standard filter set-up. The purity of the sorted population was confirmed using imaging cytometry and microscopy of cytospin preparations of sorted red blood cells infected with transgenic malaria parasites. DISCUSSION: Filter optimization is particularly important for applications where the FP signal and percentage of positive events are relatively low, such as analysis of parasite-infected samples with in the intention of gene-expression profiling and analysis. The approach outlined here results in substantially improved yield of GFP-expressing parasites, and requires decreased sorting time in comparison to standard methods. It is anticipated that this protocol will be useful for a wide range of applications involving rare events.     

A dynamical systems perspective on the relationship between symbolic and non-symbolic computation

It has been claimed that connectionist (artificial neural network) models of language processing, which do not appear to employ “rules”, are doing something different in kind from classical symbol processing models, which treat “rules” as atoms (e.g., McClelland and Patterson in Trends Cogn Sci 6(11):465–472, 2002). This claim is hard to assess in the absence of careful, formal comparisons between the two approaches. This paper formally investigates the symbol-processing properties of simple dynamical systems called affine dynamical automata, which are close relatives of several recurrent connectionist models of language processing (e.g., Elman in Cogn Sci 14:179–211, 1990). In line with related work (Moore in Theor Comput Sci 201:99–136, 1998; Siegelmann in Neural networks and analog computation: beyond the Turing limit. Birkhäuser, Boston, 1999), the analysis shows that affine dynamical automata exhibit a range of symbol processing behaviors, some of which can be mirrored by various Turing machine devices, and others of which cannot be. On the assumption that the Turing machine framework is a good way to formalize the “computation” part of our understanding of classical symbol processing, this finding supports the view that there is a fundamental “incompatibility” between connectionist and classical models (see Fodor and Pylyshyn 1988; Smolensky in Behav Brain Sci 11(1):1–74, 1988; beim Graben in Mind Matter 2(2):29--51,2004b). Given the empirical successes of connectionist models, the more general, super-Turing framework is a preferable vantage point from which to consider cognitive phenomena. This vantage may give us insight into ill-formed as well as well-formed language behavior and shed light on important structural properties of learning processes.     

An image-interpolation technique for the computation of optic flow and egomotion

 A technique for measuring the motion of a rigid, textured plane in the frontoparallel plane is developed and tested on synthetic and real image sequences. The parameters of motion – translation in two dimensions, and rotation about a previously unspecified axis perpendicular to the plane – are computed by a single-stage, non-iterative process which interpolates the position of the moving image with respect to a set of reference images. The method can be extended to measure additional parameters of motion, such as expansion or shear. Advantages of the technique are that it does not require tracking of features, measurement of local image velocities or computation of high-order spatial or temporal derivatives of the image. The technique is robust to noise, and it offers a simple, novel way of tackling the ‘aperture’ problem. An application to the computation of robot egomotion is also described. Received: 3 September 1993/Accepted in revised form: 16 April 1994     

Egomotion and relative depth map from optical flow

When an observer moves in a 3D world, optical flow fields are generated on his retina. We argue that such an observer can in principle compute the parameters of his egomotion, and following this, the relative depth map of the stationary environment solely from the instantaneous positional velocity fields (IPVF). Moreover, we argue that in the stationary world, this analysis can be done locally, and is not dependent on global properties of the optical flow under the imposed constraints (smoothness of the egomotion path, rigidity of objects, temporal continuity of perception). To investigate the method, and to analyze its performance, a computer model has been constructed which simulates an observer moving through a 3D world of stationary rectangular planes at different depths and orientations. The results suggest that the method offers a reasonable and computationally feasible means of extracting information about egomotion and surface layout from optical flows, under certain circumstances. We discuss some issues related to extending the analysis to the case of a rigid world of moving objects, and some issues related to the status of information extractable from optical flows with respect to other sources of information.     

An algorithm combining discrete and continuous methods for optical mapping.

Optical mapping is a novel technique for generating the restriction map of a DNA molecule by observing many single, partially digested copies of it, using fluorescence microscopy. The real-life problem is complicated by numerous factors: false positive and false negative cut observations, inaccurate location measurements, unknown orientations, and faulty molecules. We present an algorithm for solving the real-life problem. The algorithm combines continuous optimization and combinatorial algorithms applied to a nonuniform discretization of the data. We present encouraging results on real experimental data and on simulated data.     

In situ optical mapping of voltage and calcium in the heart

Electroanatomic mapping the interrelation of intracardiac electrical activation with anatomic locations has become an important tool for clinical assessment of complex arrhythmias. Optical mapping of cardiac electrophysiology combines high spatiotemporal resolution of anatomy and physiological function with fast and simultaneous data acquisition. If applied to the clinical setting, this could improve both diagnostic potential and therapeutic efficacy of clinical arrhythmia interventions. The aim of this study was to explore this utility in vivo using a rat model. To this aim, we present a single-camera imaging and multiple light-emitting-diode illumination system that reduces economic and technical implementation hurdles to cardiac optical mapping. Combined with a red-shifted calcium dye and a new near-infrared voltage-sensitive dye, both suitable for use in blood-perfused tissue, we demonstrate the feasibility of in vivo multi-parametric imaging of the mammalian heart. Our approach combines recording of electrophysiologically-relevant parameters with observation of structural substrates and is adaptable, in principle, to trans-catheter percutaneous approaches.     

Novel selective and non-selective optical detection of micro-organisms

A new instrument, capable of detecting metabolic changes due to microbiological activity, is described. Optical changes in growth media are monitored in a semi-fluid zone that separates the liquid medium containing the sample. Data demonstrate that common media can be utilized in conjunction with this rapid automated technology. Nutrient broth with the pH dye indicator bromocresol purple was suitable for total counts. Selective media containing dyes were utilized to assess the presence or absence of specific groups of organisms. Biochemical reactions, such as lysine decarboxylase activity, were identified by the unique generated patterns, and specific enzymatic cleavage reactions with chromogenic substrates, such as 5-bromo-4 chloro-3 indolyl-β- D -glucuronic acid (X-GLUC), were monitored.     

Optical PCR: Genomic analysis by long-range PCR and optical mapping

Optical mapping is an approach for the rapid, automated, non-electrophoretic construction of ordered restriction maps of DNA from ensembles of single molecules. Previously, we used optical mapping to make high-resolution maps of large insert clones such as bacterial artificial chromosomes (BAC) and large genomic DNA molecules. Here, we describe a combination of optical mapping and long-range polymerase chain reaction (PCR), in a process we term optical PCR, which enables automated construction of ordered restriction maps of long-range PCR products spanning human genomic loci. Specifically, we amplified three long PCR products, each averaging 14.6 kb in length, which span the 37-kb human tissue plasminogen activator (TPA) gene. PCR products were surface mounted in gridded arrays, and samples were mapped in parallel with either ScaI, XmnI, HpaI, ClaI, or BglII. A contig of overlapping high-resolution maps was generated, which agreed closely with maps predicted from sequence data. The data demonstrate an approach to construct physical maps of genomic loci where very little prior sequence information exists, since the only sequence needed is that required to anchor PCR primers. Large segments of genomic DNA (within the practical limits imposed by long-range PCR) can be mapped quickly and to high resolution without the use of cloning vectors. Received: 9 February 1999 / Accepted: 26 May 1999     

Exploring optical spectroscopic techniques and nanomaterials for virus detection

Viral infections pose significant health challenges globally by affecting millions of people worldwide and consequently resulting in a negative impact on both socioeconomic development and health. Corona virus disease 2019 (COVID-19) is a clear example of how a virus can have a global impact in the society and has demonstrated the limitations of detection and diagnostic capabilities globally. Another virus which has posed serious threats to world health is the human immunodeficiency virus (HIV) which is a lentivirus of the retroviridae family responsible for causing acquired immunodeficiency syndrome (AIDS). Even though there has been a significant progress in the HIV biosensing over the past years, there is still a great need for the development of point of care (POC) biosensors that are affordable, robust, portable, easy to use and sensitive enough to provide accurate results to enable clinical decision making. The aim of this study was to present a proof of concept for detecting HIV-1 pseudoviruses by using anti-HIV1 gp41 antibodies as capturing antibodies. In our study, glass substrates were treated with a uniform layer of silane in order to immobilize HIV gp41 antibodies on their surfaces. Thereafter, the HIV pseudovirus was added to the treated substrates followed by addition of anti-HIV gp41 antibodies conjugated to selenium nanoparticle (SeNPs) and gold nanoclusters (AuNCs). The conjugation of SeNPs and AuNCs to anti-HIV gp41 antibodies was characterized using UV–vis spectroscopy, transmission electron microscopy (TEM) and zeta potential while the surface morphology was characterized by fluorescence microscopy, atomic force microscopy (AFM) and Raman spectroscopy. The UV–vis and zeta potential results showed that there was successful conjugation of SeNPs and AuNCs to anti-HIV gp41 antibodies and fluorescence microscopy showed that antibodies immobilized on glass substrates were able to capture intact HIV pseudoviruses. Furthermore, AFM also confirmed the capturing HIV pseudoviruses and we were able to differentiate between substrates with and without the HIV pseudoviruses. Raman spectroscopy confirmed the presence of biomolecules related to HIV and therefore this system has potential in HIV biosensing applications.     

Pathogen detection: a perspective of traditional methods and biosensors

The detection of pathogenic bacteria is key to the prevention and identification of problems related to health and safety. Legislation is particularly tough in areas such as the food industry, where failure to detect an infection may have terrible consequences. In spite of the real need for obtaining analytical results in the shortest time possible, traditional and standard bacterial detection methods may take up to 7 or 8 days to yield an answer. This is clearly insufficient, and many researchers have recently geared their efforts towards the development of rapid methods. The advent of new technologies, namely biosensors, has brought in new and promising approaches. However, much research and development work is still needed before biosensors become a real and trustworthy alternative.This review not only offers an overview of trends in the area of pathogen detection but it also describes main techniques, traditional methods, and recent developments in the field of pathogen bacteria biosensors.     

Optimizing optical flow cytometry for cell volume-based sorting and analysis

Cell size is a defining characteristic central to cell function and ultimately to tissue architecture. The ability to sort cell subpopulations of different sizes would facilitate investigation at genomic and proteomic levels of mechanisms by which cells attain and maintain their size. Currently available cell sorters, however, cannot directly measure cell volume electronically, and it would therefore be desirable to know which of the optical measurements that can be made in such instruments provide the best estimate of volume. We investigated several different light scattering and fluorescence measurements in several different cell lines, sorting cell fractions from the high and low end of distributions, and measuring volume electronically to determine which sorting strategy yielded the best separated volume distributions. Since we found that different optical measurements were optimal for different cell lines, we suggest that following this procedure will enable other investigators to optimize their own cell sorters for volume-based separation of the cell types with which they work.     

Past and present concepts in flow cytometry: a European perspective

The development of flow cytometric instrumentation, methods and research concepts in Europe has been a continuous driving force for the general scientific advancement in this area over the years. This review addresses early European concepts of continuing interest with regard to instrumentation, data analysis, clinical and eperimental DNA analysis, cell function and microbiology at their worldwide first appearence while flow cytometric immunology and immunophenotyping will be covered separately. Flow cytometry represents an efficient approach to the enormous complexity of molecular cell architecture and cell function by the analysis of apparent molecular cell phenotypes in heterogeneous cell samples. The present merger of flow and image cytometry into the method independent cytomics discipline increases the potential of cell analysis very significantly. It opens the way for predictive medicine as well as for predictive cytopathology and predictive cytology in everyday clinical and medical practice. Current progress is driven by joint advances in molecular fluorescence technologies and instrument development. This complements the analysis of genome sequence information in an efficient way.     

Automated detection and mapping of electrical activation when electrogram morphology is complex

BackgroundMapping of cardiac electrical activity can be difficult when electrogram morphology is complex. Complex morphology (multiple and changing deflections) causes activation maps to vary when constructed by different analysts, particularly at areas with spatially varying conduction pattern. An algorithm was developed to automatically detect electrogram activation time which is robust to complex morphology.MethodElectrograms, many of which were complex, were collected from 320 canine epicardial border zone sites in five experiments. A library of electrogram activation times were manually marked a priori by two expert analysts. Then an algorithm which combined correlation and error functions was used to compare each input electrogram to library electrogram patterns. The closest match of input to library electrogram was used to estimate activation time. Once activation times at 320 sites were determined, activation maps were automatically constructed on a computerized grid. The algorithm was validated by comparison with activation times determined by the analysts.ResultsThe mean difference between manual and automated marking of activation time in electrograms acquired during reentrant ventricular tachycardia was 2.1 ± 3.9 ms. The mean sensitivity and positive predictive value were 95.9% and 83.8% respectively. The computer-automated marking process was completed within a few seconds and was robust to fractionated electrograms. Measurement error was mostly attributable to 60 Hz noise, which can be rectified with filtering.ConclusionsThe automated algorithm is useful for rapid and accurate automatic marking of multichannel electrograms, some of which may be fractionated, as well as for real-time display of activation maps in clinical electrophysiology or research studies.