117 resultados para Imaging segmentation
em Indian Institute of Science - Bangalore - Índia
Resumo:
Imaging flow cytometry is an emerging technology that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy. It allows high-throughput imaging of cells with good spatial resolution, while they are in flow. This paper proposes a general framework for the processing/classification of cells imaged using imaging flow cytometer. Each cell is localized by finding an accurate cell contour. Then, features reflecting cell size, circularity and complexity are extracted for the classification using SVM. Unlike the conventional iterative, semi-automatic segmentation algorithms such as active contour, we propose a noniterative, fully automatic graph-based cell localization. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using custom fabricated cost-effective microfluidics-based imaging flow cytometer. The proposed system is a significant development in the direction of building a cost-effective cell analysis platform that would facilitate affordable mass screening camps looking cellular morphology for disease diagnosis. Lay description In this article, we propose a novel framework for processing the raw data generated using microfluidics based imaging flow cytometers. Microfluidics microscopy or microfluidics based imaging flow cytometry (mIFC) is a recent microscopy paradigm, that combines the statistical power of flow cytometry with spatial and quantitative morphology of digital microscopy, which allows us imaging cells while they are in flow. In comparison to the conventional slide-based imaging systems, mIFC is a nascent technology enabling high throughput imaging of cells and is yet to take the form of a clinical diagnostic tool. The proposed framework process the raw data generated by the mIFC systems. The framework incorporates several steps: beginning from pre-processing of the raw video frames to enhance the contents of the cell, localising the cell by a novel, fully automatic, non-iterative graph based algorithm, extraction of different quantitative morphological parameters and subsequent classification of cells. In order to evaluate the performance of the proposed framework, we have successfully classified unstained label-free leukaemia cell-lines MOLT, K562 and HL60 from video streams captured using cost-effective microfluidics based imaging flow cytometer. The cell lines of HL60, K562 and MOLT were obtained from ATCC (American Type Culture Collection) and are separately cultured in the lab. Thus, each culture contains cells from its own category alone and thereby provides the ground truth. Each cell is localised by finding a closed cell contour by defining a directed, weighted graph from the Canny edge images of the cell such that the closed contour lies along the shortest weighted path surrounding the centroid of the cell from a starting point on a good curve segment to an immediate endpoint. Once the cell is localised, morphological features reflecting size, shape and complexity of the cells are extracted and used to develop a support vector machine based classification system. We could classify the cell-lines with good accuracy and the results were quite consistent across different cross validation experiments. We hope that imaging flow cytometers equipped with the proposed framework for image processing would enable cost-effective, automated and reliable disease screening in over-loaded facilities, which cannot afford to hire skilled personnel in large numbers. Such platforms would potentially facilitate screening camps in low income group countries; thereby transforming the current health care paradigms by enabling rapid, automated diagnosis for diseases like cancer.
Resumo:
Digital holography is the direct recording of holograms using a CCD camera and is an alternative to the use of a film or a plate. In this communication in-line digital holographic microscopy has been explored for its application in particle imaging in 3D. Holograms of particles of about 10 mu m size have been digitally reconstructed. Digital focusing was done to image the particles in different planes along the depth of focus. Digital holographic particle imaging results were compared with conventional optical microscope imaging. A methodology for dynamic analysis of microparticles in 3D using in-line digital holography has been proposed.
Resumo:
A defect-selective photothermal imaging system for the diagnostics of optical coatings is demonstrated. The instrument has been optimized for pump and probe parameters, detector performance, and signal processing algorithm. The imager is capable of mapping purely optical or thermal defects efficiently in coatings of low damage threshold and low absorbance. Detailed mapping of minor inhomogeneities at low pump power has been achieved through the simultaneous action of a low-noise fiber optic photothermal beam defection sensor and a common-mode-rejection demodulation (CMRD) technique. The linearity and sensitivity of the sensor have been examined theoretically and experimentally, and the signal to noise ratio improvement factor is found to be about 110 compared to a conventional bicell photodiode. The scanner is so designed that mapping of static or shock sensitive samples is possible. In the case of a sample with absolute absorptance of 3.8 x 10(-4), a change in absorptance of about 0.005 x 10(-4) has been detected without ambiguity, ensuring a contrast parameter of 760. This is about 1085% improvement over the conventional approach containing a bicell photodiode, at the same pump power. The merits of the system have been demonstrated by mapping two intentionally created damage sites in a MgF2 coating on fused silica at different excitation powers. Amplitude and phase maps were recorded for thermally thin and thick cases, and the results are compared to demonstrate a case which, in conventional imaging, would lead to a deceptive conclusion regarding the type and location of the damage. Also, a residual damage profile created by long term irradiation with high pump power density has been depicted.
Resumo:
We study by means of experiments and Monte Carlo simulations, the scattering of light in random media, to determine the distance up to which photons travel along almost undeviated paths within a scattering medium, and are therefore capable of casting a shadow of an opaque inclusion embedded within the medium. Such photons are isolated by polarisation discrimination wherein the plane of linear polarisation of the input light is continuously rotated and the polarisation preserving component of the emerging light is extracted by means of a Fourier transform. This technique is a software implementation of lock-in detection. We find that images may be recovered to a depth far in excess of that predicted by the diffusion theory of photon propagation. To understand our experimental results, we perform Monte Carlo simulations to model the random walk behaviour of the multiply scattered photons. We present a. new definition of a diffusing photon in terms of the memory of its initial direction of propagation, which we then quantify in terms of an angular correlation function. This redefinition yields the penetration depth of the polarisation preserving photons. Based on these results, we have formulated a model to understand shadow formation in a turbid medium, the predictions of which are in good agreement with our experimental results.
Resumo:
Micro-Raman imaging of the distribution of Te precipitates in CdZnTe crystals in different phases is reported. For the normal phase of Te precipitates, the Raman modes appear centered around 121(A1), 141(E)/TO(CdTe) cm−1 and a weak mode around 92(E) cm−1 in CdZnTe indicating the presence of trigonal lattice of Te. Under high pressure phase, the volume of Te precipitates collapses, giving more bond energy resulting in the blueshift of the corresponding Raman bands. Also, the spatial distribution of the area ratio of 121 to 141 cm−1 Raman modes is used to quantify Te precipitates. Further, near-infrared microscopy images support these results.
Resumo:
A new photothermal imaging process which utilizes no silver has been demonstrated in obliquely deposited Se-Ge films. Band-gap irradiation of Se-Ge films has been found to give rise to phases of the type SeOx, GeO, and Se as borne by x-ray initiated Auger electron spectroscopy and x-ray photoelectron spectroscopy. Annealing of SeOx leads to the formation of SeO2. The large (several orders of magnitude) difference in vapor pressures of SeO2 and Se-Ge films results in differential evaporation of the films when annealed around 200 °C, thereby leading to imaging. Such a large contrast in evaporation rates between the exposed and unexposed regions has great potential applications in high resolution image storage and phase holography. Applied Physics Letters is copyrighted by The American Institute of Physics.
Resumo:
This paper deals with new results obtained in regard to the reconstruction properties of side-band Fresnel holograms (SBFH) of self-imaging type objects (for example, gratings) as compared with those of general objects. The major finding is that a distribution I2, which appears on the real-image plane along with the conventional real-image I1, remains a 2Z distribution (where 2Z is the axial distance between the object and its self-imaging plane) under a variety of situations, while its nature and focusing properties differ from one situation to another. It is demonstrated that the two distributions I1 and I2 can be used in the development of a novel technique for image subtraction.
Resumo:
Through an analysis using the transfer function of a pinhole camera, the multiple imaging characteristics of photographic diffusers described by Grover and Tremblay [Appl. Opt.21,4500(1982)] is studied. It is found that only one pinhole diameter satisfies the optimum imaging condition for best contrast transfer at any desired spatial frequency. A simple method of generating random pinhole arrays with a controlled pinhole diameter is described. These pinhole arrays are later used to generate high frequency sinusoidal gratings from a coarse grid. The contrast in the final gratings is found to be reasonably high.
Resumo:
We propose a self-regularized pseudo-time marching strategy for ill-posed, nonlinear inverse problems involving recovery of system parameters given partial and noisy measurements of system response. While various regularized Newton methods are popularly employed to solve these problems, resulting solutions are known to sensitively depend upon the noise intensity in the data and on regularization parameters, an optimal choice for which remains a tricky issue. Through limited numerical experiments on a couple of parameter re-construction problems, one involving the identification of a truss bridge and the other related to imaging soft-tissue organs for early detection of cancer, we demonstrate the superior features of the pseudo-time marching schemes.
Resumo:
In this paper we discuss a new technique to image the surfaces of metallic substrates using field emission from a pointed array of carbon nanotubes (CNTs). We consider a pointed height distribution of the CNT array under a diode configuration with two side gates maintained at a negative potential to obtain a highly intense beam of electrons localized at the center of the array. The CNT array on a metallic substrate is considered as the cathode and the test substrate as the anode. Scanning the test Substrate with the cathode reveals that the field emission current is highly sensitive to the surface features with nanometer resolution. Surface features of semi-circular, triangular and rectangular geometries (projections and grooves) are considered for simulation. This surface scanning/mapping technique can be applied for surface roughness measurements with nanoscale accuracy. micro/nano damage detection, high precision displacement sensors, vibrometers and accelerometers. among other applications.
Resumo:
[1] We have compared the spectral aerosol optical depth (AOD, tau lambda) and aerosol fine mode fraction (AFMF) of Collection 004 (C004) derived from Moderate-Resolution Imaging Spectroradiometer (MODIS) on board National Aeronautics and Space Administration's (NASA) Terra and Aqua platforms with that obtained from Aerosol Robotic Network (AERONET) at Kanpur (26.45 degrees N, 80.35 degrees E), India for the period 2001-2005. The spatially-averaged (0.5 degrees x 0.5 degrees centered at AERONET sunphotometer) MODIS Level-2 aerosol parameters (10 km at nadir) were compared with the temporally averaged AERONET-measured AOD (within +/- 30 minutes of MODIS overpass). We found that MODIS systematically overestimated AOD during the pre-monsoon season (March to June, known to be influenced by dust aerosols). The errors in AOD at 0.66 mu m were correlated with the apparent reflectance at 2.1 mu m (rho*(2.1)) which MODIS C004 uses to estimate the surface reflectance in the visible channels (rho(0.47) = rho*(2.1)/ 4, rho(0.66) = rho*(2.1)/ 2). The large errors in AOD (Delta tau(0.66) > 0.3) are found to be associated with the higher values of rho*(2.1) (0.18 to 0.25), where the uncertainty in the ratios of reflectance is large (Delta rho(0.66) +/- 0.04, Delta rho(0.47) +/- 0.02). This could have resulted in lower surface reflectance, higher aerosol path radiance and thus lead to overestimation in AOD. While MODIS-derived AFMF has binary distribution (1 or 0) with too low (AFMF < 0.2) during dust-loading period, and similar to 1 for the rest of the retrievals, AERONET showed range of values (0.4 to 0.9). The errors in tau(0.66) were also high in the scattering angle range 110 degrees - 140 degrees, where the optical effects of nonspherical dust particles are different from that of spherical particles.
Resumo:
We describe a novel method for human activity segmentation and interpretation in surveillance applications based on Gabor filter-bank features. A complex human activity is modeled as a sequence of elementary human actions like walking, running, jogging, boxing, hand-waving etc. Since human silhouette can be modeled by a set of rectangles, the elementary human actions can be modeled as a sequence of a set of rectangles with different orientations and scales. The activity segmentation is based on Gabor filter-bank features and normalized spectral clustering. The feature trajectories of an action category are learnt from training example videos using dynamic time warping. The combined segmentation and the recognition processes are very efficient as both the algorithms share the same framework and Gabor features computed for the former can be used for the later. We have also proposed a simple shadow detection technique to extract good silhouette which is necessary for good accuracy of an action recognition technique.
Resumo:
A popular dynamic imaging technique, k-t BLAST (ktB) is studied here for BAR imaging. ktB utilizes correlations in k-space and time, to reconstruct the image time series with only a fraction of the data. The algorithm works by unwrapping the aliased Fourier conjugate space of k-t (y-f-space). The unwrapping process utilizes the estimate of the true y-f-space, by acquiring densely sampled low k-space data. The drawbacks of this method include separate training scan, blurred training estimates and aliased phase maps. The proposed changes are incorporation of phase information from the training map and using generalized-series-extrapolated training map. The proposed technique is compared with ktB on real fMRI data. The proposed changes allow for ktB to operate at an acceleration factor of 6. Performance is evaluated by comparing activation maps obtained using reconstructed images. An improvement of up to 10 dB is observed in thePSNR of activation maps. Besides, a 10% reduction in RMSE is obtained over the entire time series of fMRI images. Peak improvement of the proposed method over ktB is 35%, averaged over five data sets. (C)2010 Elsevier Inc. All rights reserved.
Resumo:
This paper describes a method of automated segmentation of speech assuming the signal is continuously time varying rather than the traditional short time stationary model. It has been shown that this representation gives comparable if not marginally better results than the other techniques for automated segmentation. A formulation of the 'Bach' (music semitonal) frequency scale filter-bank is proposed. A comparative study has been made of the performances using Mel, Bark and Bach scale filter banks considering this model. The preliminary results show up to 80 % matches within 20 ms of the manually segmented data, without any information of the content of the text and without any language dependence. 'Bach' filters are seen to marginally outperform the other filters.