Pixel Plane Research Articles

Dedicated low-field MRI in mice

The rationale of this work is to point out the relevance of in vivo MR images of mice obtained using a dedicated low-field system. For this purpose a small 0.1 T water-cooled electro-magnet and solenoidal radio frequency (RF) transmit–receive coils were used. All MR images were acquired in three-dimensional (3D) mode. An isolation cell was designed allowing easy placement of the RF coils and simple delivery of gaseous anesthesia as well as warming of the animal. Images with and without contrast agent were obtained in total acquisition times on the order of half an hour to four hours on normal mice as well as on animals bearing tumors. Typical in plane pixel dimensions range from 200 × 200 to 500 × 500 µm2 with slice thicknesses ranging between 0.65 and 1.50 mm. This work shows that, besides light installation and low cost, dedicated low-field MR systems are suitable for small rodents imaging, opening this technique even to small research units.

Shrinkage Kinetics during Convective Drying of Selected Berries

Drying and shrinkage kinetics of gooseberry, black and red currants, cherry, and blackberry were studied using a fully automated experimental apparatus, designed for continuous monitoring of the material moisture content, its temperature, and surface area. Experimental drying curves were approximated with a modified exponential model. The volume and surface area of berries were determined from the pictures taken during drying and transformed into digital images. The procedure for calculation of the object-related pixels in a two-dimensional plane to the temporal three-dimensional volume and surface area of the berries was developed. The modified exponential model was proposed to correlate the volumetric and surface area shrinkage with moisture content. Volumetric shrinkage at the end of drying was maximal (0.3) for black currant and minimal (0.45) for gooseberry.

3D Data Acquisition and Reconstruction from SEM Stereo Pairs

The image processing technology has now been widely applied into many areas such as electronics, manufacturing and security. However, most of those applications are based on two dimensional images. Recently, there are increasing demands of 3D information for new applications. The incoming visual information via a digital imaging device (ex. CCD) is digitized into pixels in plane with color/gray scale. Each pixel contains 2D positional information, the CCD thus offers an 2D orthogonal coordinate, but loses the 3rd dimension in depth for objects in view. The aim of this research is to develop an algorithm for acquisition and configuration of 3D information by means of binocular stereo vision. In this paper, the 3D data acquisition and reconstruction are demonstrated at static SEM stereopairs. Also the accuracy of acquired data is discussed.

Pre-processing considerations of IRS-P6 LISS-4 imagery

Wide image swath with a high geometric resolution is required for photogrammetric applications. Both demands can be satisfied using staggered line arrays. Different bands of IRS-P6 LISS-4 sensor use staggered arrays for imaging. This paper describes a method for computing the offset for geometric alignment of odd and even lines of the staggered array of IRS-P6 LISS-4 imagery. The odd and even pixel rows are separated by 35μm (equal to 5 pixels) in the focal plane in the along-track direction. Slightly different viewing angles of both lines of a staggered array can result in a variable sampling pattern on the ground because of the attitude fluctuations, satellite movement, terrain topography, PSM steering and small variations in the angular placement of the CCD lines (from the pre-launch values) in the focal plane. Non-accounting of this variable sampling value during the video data alignment will introduce deterioration of image quality and geometric discontinuity of features. The stagger parameters can be computed by the reconstruction of the viewing geometry with a calibrated camera geometry model and a public domain DEM. The impact of the line separation in the focal plane during imaging for different viewing configurations and terrain heights are studied and reported in this paper. Computed values from the model are in good agreement with what is observed in the raw image for different view angles. The results verify the model and are representative of the stability of the platform.

Pixelation Effects in Weak Lensing

ABSTRACTWeak gravitational lensing can be used to investigate both dark matter and dark energy but requires accurate measurements of the shapes of faint, distant galaxies. Such measurements are hindered by the finite resolution and pixel scale of digital cameras. We investigate the optimum choice of pixel scale for a space‐based mission, using the engineering model and survey strategy of the proposed Supernova Acceleration Probe as a baseline. We do this by simulating realistic astronomical images containing a known input shear signal and then attempting to recover the signal using the Rhodes, Refregier, & Groth algorithm. We find that the quality of shear measurement is always improved by smaller pixels. However, in practice, telescopes are usually limited to a finite number of pixels and operational life span, so the total area of a survey increases with pixel size. We therefore fix the survey lifetime and the number of pixels in the focal plane while varying the pixel scale, thereby effectively varying the survey size. In a pure trade‐off for image resolution versus survey area, we find that measurements of the matter power spectrum would have minimum statistical error with a pixel scale of 0.09″ for a 0.14″ FWHM point‐spread function (PSF). The pixel scale could be increased to ∼0.16″ if images dithered by exactly half‐pixel offsets were always available. Some of our results do depend on our adopted shape measurement method and should be regarded as an upper limit: future pipelines may require smaller pixels to overcome systematic floors not yet accessible, and, in certain circumstances, measuring the shape of the PSF might be more difficult than those of galaxies. However, the relative trends in our analysis are robust, especially those of the surface density of resolved galaxies. Our approach thus provides a snapshot of potential in available technology, and a practical counterpart to analytic studies of pixelation, which necessarily assume an idealized shape measurement method.

The infinitesimal operator for the semigroup of the Frobenius-Perron operator from image sequence data: Vector fields and transport barriers from movies

In this paper, we present an approach to approximate the Frobenius-Perron transfer operator from a sequence of time-ordered images, that is, a movie dataset. Unlike time-series data, successive images do not provide a direct access to a trajectory of a point in a phase space; more precisely, a pixel in an image plane. Therefore, we reconstruct the velocity field from image sequences based on the infinitesimal generator of the Frobenius-Perron operator. Moreover, we relate this problem to the well-known optical flow problem from the computer vision community and we validate the continuity equation derived from the infinitesimal operator as a constraint equation for the optical flow problem. Once the vector field and then a discrete transfer operator are found, then, in addition, we present a graph modularity method as a tool to discover basin structure in the phase space. Together with a tool to reconstruct a velocity field, this graph-based partition method provides us with a way to study transport behavior and other ergodic properties of measurable dynamical systems captured only through image sequences.

New systolic array processor architecture for simultaneous discrete convolution of an image plane with multiple filter coefficient sets

A new high-performance scalable systolic array processor architecture module for implementation of the two-dimensional discrete convolution algorithm on an (i×j) pixel input image plane (IP) using an (n×n) filter coefficient (FC) plane is first presented. The module generates one convoluted output image (OI) plane pixel per system clock cycle for an (n×n) FC plane using a level of r hardware resources. Second, the architecture is extended in a modular scalable manner to allow simultaneous convolution of a single IP, with k different (n×n) FC planes, such that k convoluted OI plane pixels are generated each system clock cycle, utilizing less than (k*r) hardware resources. The new convolution architecture may be implemented to an ASIC or programmable logic device (PLD) platform. Results of synthesizing and implementing the proposed architecture are shown, illustrating the scalability of the new convolution architecture relative to k. Results from postimplementation virtual hardware prototype simulation testing and from testing a PLD-based experimental hardware prototype are shown that validate correct functional and performance operation of the new convolution architecture module.

Computer-aided Classification of Interstitial Lung Diseases Via MDCT: 3D Adaptive Multiple Feature Method (3D AMFM)

Computer-aided detection algorithms applied to multidetector row CT (MDCT) lung image data sets have the potential to significantly alter clinical practice through the early, quantitative detection of pulmonary pathology. In this project, we have further developed a computer-aided detection tool, the adaptive multiple feature method (AMFM), for the detection of interstitial lung diseases based on MDCT-generated volumetric data. We performed MDCT (Siemens Sensation 16 or 64 120 kV, B50f convolution kernel, and <or=0.75-mm slice thickness) on 20 human volunteers recruited from four cohorts studied under an National Institutes of Health-sponsored Bioengineering Research Partnership Grant: 1) normal never smokers; 2) normal smokers; 3) those with emphysema, and 4) those with interstitial lung disease (total: 11 males, 9 females; age range 20-75 years, mean age 40 years). A total of 1,184 volumes of interest (VOIs; 21 x 21 pixels in plane) were marked by a senior radiologist and a senior pulmonologist as emphysema (EMPH, n = 287); ground-glass (GG, n = 147), honeycombing (HC, n = 137), normal nonsmokers (NN, n = 287), and normal smokers (NS, n = 326). For each VOI, we calculated 24 volumetric features, including statistical features (first-order features, run-length, and co-occurrence features), histogram, and fractal features. We compared two methods of classification (a Support Vector Machine (SVM) and a Bayesian classifier) using a 10-fold cross validation method and McNemar's test. The sensitivity of five patterns in the form of Bayesian/SVM was: EMPH: 91/93%; GG: 89/86%; HC: 93/90%; NN: 90/73%; and NS: 75/82%. The specificity of five patterns in the form of Bayesian/support vector machine was: EMPH: 98/98%; GG: 98/98%; HC: 99/99%; NN: 90/94%; and NS: 96/91%. We conclude that volumetric features including statistical features, histogram and fractal features can be successfully used in differentiation of parenchymal pathology associated with both emphysema and interstitial lung diseases. Additionally, support vector machine and Bayesian methods are comparable classifiers for characterization of interstitial lung diseases on MDCT images.

Monocular obstacle detection using reciprocal-polar rectification

Our obstacle detection method is applicable to deliberative translation motion of a mobile robot and, in such motion, the epipole of each image of an image pair is coincident and termed the focus of expansion (FOE). We present an accurate method for computing the FOE and then we use this to apply a novel rectification to each image, called a reciprocal-polar (RP) rectification. When robot translation is parallel to the ground, as with a mobile robot, ground plane image motion in RP-space is a pure shift along an RP image scan line and hence can be recovered by a process of 1D correlation, even over large image displacements and without the need for corner matches. Furthermore, we show that the magnitude of these shifts follows a sinusoidal form along the second (orientation) dimension of the RP image. This gives the main result that ground plane motion over RP image space forms a 3D sinusoidal manifold. Simultaneous ground plane pixel grouping and recovery of the ground plane motion thus amounts to finding the FOE and then robustly fitting a 3D sinusoid to shifts of maximum correlation in RP space. The phase of the recovered sinusoid corresponds to the orientation of the vanishing line of the ground plane and the amplitude is related to the magnitude of the robot/camera translation. Recovered FOE, vanishing line and sinusoid amplitude fully define the ground plane motion (homography) across a pair of images and thus obstacles and ground plane can be segmented without any explicit knowledge of either camera parameters or camera motion.

First look at the beam test results of the FPIX2 readout chip for the BTeV silicon pixel detector

High energy and nuclear physics experiments need tracking devices with increasing spatial precision and readout speed in the face of ever-higher track densities and increased radiation environments. The new generation of hybrid pixel detectors (arrays of silicon diodes bump bonded to arrays of front-end electronic cells) is the technology able to meet these challenges. We report the first results of the BTeV silicon pixel detector beam test carried out at Fermilab in summer 2004. Tests were performed using a 120 GeV/c proton beam incident on a 6 plane pixel detector telescope. The last prototype developed for the BTeV experiment (FPIX2) is tested in the middle of the telescope. There is no external trigger, and events were built using the time-stamp information provided by the readout chips

Parametric indices of fuzziness for automated image enhancement

This paper presents an automated fuzziness-driven algorithm for image enhancement. A class of parametric indices of fuzziness is introduced, which serves as the optimization criterion of the contrast-enhancement procedure. We show that the parametric class of indices constitutes a one-parameter generalization of the linear index of fuzziness of a set. The modification of the membership values of image pixels in the fuzzy plane is performed by finding the optimal S-function, which maximizes the parametric index of fuzziness (PIF). The first-order fuzzy moment of the image is used for tuning the PIF. Experimental results demonstrate the efficiency of the proposed framework in enhancing even highly low-contrasted images and also its ability to improve existing contrast-enhancing algorithms.

Equiresolution catadioptric sensors

A prominent characteristic of most catadioptric sensors is their lack of uniformity of resolution. We describe catadioptric sensors whose associated projections from the viewing sphere to the image plane have constant Jacobian determinants and so are equiresolution in the sense that any two equal solid angles are allocated the same number of pixels in the image plane. We show that in the orthographic case the catoptric component must be a surface of revolution of constant Gaussian curvature. We compare these equiresolution sensors in both the perspective and orthographic cases with other sensors that were proposed earlier for treating the uniformity-of-resolution problem.

A CMOS floating-gate matrix transform imager

A new transform imager technology and architecture is introduced in this paper. This approach allows for retina and higher-level bio-inspired computation in a programmable architecture that still possesses similar high-fill factor pixels of APS imagers. This imager is capable of programmable matrix operations on the image, where the image can be presented as either a full matrix or using block matrix operations. Each pixel is composed of a photodiode sensor element and a multiplier. The core imager performs computation at the pixel plane but still holds to a fill factor greater than 46 %. The resulting data-flow architecture directly allows computation of spatial transforms, motion computations, and stereo computations.

Quantum cascade detectors

A photovoltaic intersubband detector based on electron transfer on a cascade of quantum levels is presented which we called a Quantum Cascade Detector (QCD). The highest photoresponse of intersubband transition based photovoltaic detectors is demonstrated: 44 mA/W at zero applied bias. Further improvements permit to suppress the leakage current and to increase the resistivity R 0 A. Useless cross-transitions have been eliminated finally leading to a high resistance narrow band photodetector with a Johnson noise limited detectivity at 50 K comparable to QWIPs. Because they work with no dark current, QCDs are very promising for small pixel and large focal plane array applications.

High resistance narrow band quantum cascade photodetectors

A high resistance narrow band quantum cascade photodetector (QCD) is presented. Leakage current has been suppressed, increasing the resistivity, thanks to a design in which coupling barriers have been thickened. Useless cross transitions have been eliminated finally leading to a Johnson noise detectivity at 50 K comparable to quantum well infrared photodetectors. Because they work with no dark current, QCDs are very promising for small pixel and large focal plane array applications.

High Fill-Factor Imagers for Neuromorphic Processing Enabled by Floating-Gate Circuits

In neuromorphic modeling of the retina, it would be very nice to have processing capabilities at the focal plane while retaining the density of typical active pixel sensor (APS) imager designs. Unfortunately, these two goals have been mostly incompatible. We introduce our transform imager technology and basic architecture that uses analog floating-gate devices to make it possible to have computational imagers with high pixel densities. This imager approach allows programmable focal-plane processing that can perform retinal and higher-level bioinspired computation. The processing is performed continuously on the image via programmable matrix operations that can operate on the entire image or blocks within the image. The resulting dataflow architecture can directly perform computation of spatial transforms, motion computations, and stereo computations. The core imager performs computations at the pixel plane, but still holds a fill factor greater than 40 percent—comparable to the high fill factors of APS imagers. Each pixel is composed of a photodiode sensor element and a multiplier. We present experimental results from several imager arrays built in 0.5 m process (up to in an area of 4 millimeter squared).

Analysis of factors affecting positron emission mammography (PEM) image formation

Image reconstruction for positron emission mammography (PEM) with two parallel, planar detectors is usually performed by backprojection to image planes. Three major factors affecting backprojection image reconstruction are investigated: 1) image uniformity (flood) corrections; 2) image sampling (pixel size); and 3) count allocation methods. An analytic expression for uniformity correction is developed that incorporates factors for spatial-dependent detector sensitivity and geometric effects from acceptance angle limits on coincidence events. There is good agreement between experimental uniformity correction images and numerical simulations. The analytic uniformity corrections are successfully applied to image reconstruction of breast phantoms and reduce the need for multiple flood scans. Experimental and simulated breast phantom studies show that lesion contrast is improved when the image pixel size is half of, rather than equal to, the detector pixel size, at the expense of some additional image noise. In PEM reconstruction counts usually are allocated to the pixel in the image plane intersected by the line of response (LOR) between the centers of the detection pixels. An alternate count allocation method is investigated that distributes counts to image pixels in proportion to the area of the tube of response (TOR) connecting the detection pixels that they overlay in the image plane. This TOR method eliminates some image artifacts and increases tumor signal-to-noise ratios (SNRs) at the expense of a slight decrease in tumor contrast. Image reconstruction by the iterative maximum likelihood expectation maximization (MLEM) method also is investigated. MLEM reconstruction improves the tumor contrast and SNR compared with the backprojection method. Further work is required to optimize reconstruction parameters for particular detection or quantitation tasks.

Fast coordinates generating circuit for pixel parallel processing

AbstractSince the coordinates of multiple points cannot be encoded simultaneously due to the encoder characteristics when encoding the positions of multiple points on a plane as the coordinates, each point must be successively searched for, and each coordinate must be encoded in order. Highly efficient algorithms to search for points on a plane, such as the binary search, are known. These algorithms can be easily implemented in software in general, but are difficult to implement in hardware. In this paper, we propose an algorithm that rapidly searches for the points on a plane and its circuit architecture in order to encode multiple points. We used this proposed circuit in the last stage of a circuit that detects the centroids of objects on a pixel plane and searched for the detected centroids by a circuit simulation in H‐SPICE. From the result, we verified the completion of the search of a 15 × 15‐pixel plane in several microseconds. Since the processing time of this algorithm depends, in theory, on the number of points to be searched for and not on the number of pixels on the pixel plane, even as the number of pixels on the pixel plane to be searched increases, the processing time does not increase dramatically. Therefore, this algorithm is also effective as the resolution improves. © 2002 Wiley Periodicals, Inc. Electron Comm Jpn Pt 2, 85(6): 27–32, 2002; Published online in Wiley InterScience (www.interscience.wiley.com). DOI 10.1002/ecjb.1109

Theoretical limits of scanning white-light interferometry signal evaluation algorithms

Scanning white-light interferometry is widely used for the microstructure analysis of technical and biological specimens. For each pixel in the focal plane of the apparatus a white-light interferogram is acquired and evaluated by means of an algorithm. We discuss some properties of mathematically optimal evaluation methods and the best possible achievable resolution derived therefrom depending on the setup parameters. A comparison of the results to one of the algorithms described in the literature is given.

A new design for a high resolution, high efficiency CZT gamma camera detector

We have designed a CZT gamma camera detector that provides an array of CZT pixels and associated front-end electronics – including an ASIC – and permits gamma camera measurements using the method patented by CEA-LETI and reported by Verger et al. [1]. Electron response in each CZT pixel is registered by correcting pulse height for position of interaction based on fast rise-time information. This method brings advantages of high scatter rejection while allowing high detection efficiency. These techniques and the systems approach have been developed at CEA-LETI in an exclusive joint development with BICRON and CRISMATEC who in turn are commercializing the technology. The initial system is implemented in an array framework with 1920 pixels, approximately 180×215 mm 2 in dimension, but the system architecture expands readily to 4096 pixels, and these arrays can be ganged into groups of up to 8 for pixel planes totaling over 32 000 pixels without architecture changes. The overall system design is described and brain phantom images are presented that were obtained by scanning with a small number of pixels.