Multimedia, including audio, image, and video, etc., is a ubiquitous part of modern life. Quality evaluation, both objective and subjective, is of fundamental importance for various multimedia applications. In this letter, a novel quality-aware feature is proposed for blind/no-reference (NR) image quality assessment (IQA). The new quality-aware feature is generated from the proposed joint generalized local binary pattern (GLBP) statistics. In this method, using the Laplacian of Gaussian (LOG) filters, the images are first decomposed into multi-scale subband images. Then, the subband images are encoded with the proposed GLBP operator and the quality-aware features are formed from the joint GLBP histograms from the encoding maps of each subband image. Finally, using support vector regression (SVR), the quality-aware features are mapped to the image's subjective quality score for NR-IQA. The experimental results for two representative databases show that the proposed method is strongly correlated to subjective quality evaluations and competitive to the state-of-the-art NR-IQA methods.

Multimedia, including audio, image and video, etc, is a ubiquitous part of modern life. Evaluations, both objective and subjective, are of fundamental importance for numerous multimedia applications. In this paper, based on statistics of local binary pattern (LBP), we propose a novel and efficient quality similarity index for no reference (NR) image quality assessment (IQA). First, with the Laplacian of Gaussian (LOG) filters, the image is decomposed into multi-scale sub-band images. Then, for these sub-band images across different scales, LBP maps are encoded and the LBP histograms are formed as the quality assessment concerning feature. Finally, by support vector regression (SVR), the extracted features are mapped to the image's subjective quality score for NR IQA. The experimental results on LIVE IQA database show that the proposed method is strongly related to subjective quality evaluations and competitive to most of the state-of-the-art NR IQA methods.

Microaneurysm in the retina is one of the signs of simple diabetic retinopathy. We have been investigating a computerized method for the detection of microaneurysms on retinal fundus images. In this study, the computerized scheme was developed by using twenty five cases. After image preprocessing, candidate regions for microaneurysms were detected using a double-ring filter. Any potential false positives located in the regions corresponding to blood vessels were removed by automatic extraction of blood vessels from the images. One hundred twenty six image features were determined, and 28 components were selected by using principal component analysis, and the candidate lesions were classified into microaneurysms or false positives using the rule-based method and an artificial neural network. The true positive rate of the proposed method was 68% at 15 false positives per image.

The detection of microaneurysms in digital color fundus photographs is a critical first step in automated screening for diabetic retinopathy (DR), a common complication of diabetes. To accomplish this detection numerous methods have been published in the past but none of these was compared with each other on the same data. In this work we present the results of the first international microaneurysm detection competition, organized in the context of the Retinopathy Online Challenge (ROC), a multiyear online competition for various aspects of DR detection. For this competition, we compare the results of five different methods, produced by five different teams of researchers on the same set of data. The evaluation was performed in a uniform manner using an algorithm presented in this work. The set of data used for the competition consisted of 50 training images with available reference standard and 50 test images where the reference standard was withheld by the organizers (M. Niemeijer, B. van Ginneken, and M. D. Abràmoff). The results obtained on the test data was submitted through a website after which standardized evaluation software was used to determine the performance of each of the methods. A human expert detected microaneurysms in the test set to allow comparison with the performance of the automatic methods. The overall results show that microaneurysm detection is a challenging task for both the automatic methods as well as the human expert. There is room for improvement as the best performing system does not reach the performance of the human expert. The data associated with the ROC microaneurysm detection competition will remain publicly available and the website will continue accepting submissions.

Shape correspondence, which aims at accurately identifying corresponding landmarks from a given population of shape instances, is a very challenging step in constructing a statistical shape model such as the Point Distribution Model. The state-of-the-art methods such as MDL and SPHARM are primarily focused on closed-surface shape correspondence. In this paper we develop a novel method aimed at identifying accurately corresponding landmarks on 3D open-surfaces with a closed boundary. In particular, we enforce explicit topology consistency on the identified landmarks to ensure that they form a simple, consistent triangle mesh to more accurately model the correspondence of the underlying continuous shape instances. The proposed method also ensures the correspondence of the boundary of the open surfaces. For our experiments, we test the proposed method by constructing a statistical shape model of the human diaphragm from 26 shape instances.

Accurately identifying corresponded landmarks from a population of shape instances is the major challenge in constructing statistical shape models. In this paper, we address this landmark-based shape-correspondence problem for 3D cases by developing a highly efficient landmark-sliding algorithm. This algorithm is able to quickly refine all the landmarks in a parallel fashion by sliding them on the 3D shape surfaces. We use 3D thin-plate splines to model the shape-correspondence error so that the proposed algorithm is invariant to affine transformations and more accurately reflects the nonrigid biological shape deformations between different shape instances. In addition, the proposed algorithm can handle both open-and closed-surface shape, while most of the current 3D shape-correspondence methods can only handle genus-0 closed surfaces. We conduct experiments on 3D hippocampus data and compare the performance of the proposed algorithm to the state-of-the-art MDL and SPHARM methods. We find that, while the proposed algorithm produces a shape correspondence with a better or comparable quality to the other two, it takes substantially less CPU time. We also apply the proposed algorithm to correspond 3D diaphragm data which have an open-surface shape.

High-density LSI packages such as ball grid array (BGA) are being utilised in the car electronics and communications infrastructure products. These products require a high-speed and reliable inspection technique for their solder joints. In this paper, we propose an automated X-ray inspection technique for BGA mounted substrate based on oblique computed tomography (OCT). Automated inspection consists of OCT capturing, position adjustment, bump extraction, character extraction and judgment. We proposed five characteristic features related to the bump shape. Moreover, by combining the characteristic features using artificial neural network, the condition of a solder bump was determined. In the experiments, we evaluate these techniques using actual BGA-mounted substrate. As a result, the correct rate of judgment reached 99.7%, which shows the clearly indicates that our method may be useful in the practice.

Recently, we have been developing several automated algorithms for detecting masses on mammograms. For our algorithm, we devised an adaptive thresholding technique for detecting masses, but our system failed to detect masses with a partial loss of region that were located on the edge of the film. This is a common issue in all of the algorithms developed so far by other groups. In order to deal with this problem, we propose a new method in the present study. The partial loss masses are identified by their similarity to a sector-form model in the template matching process. To calculate the similarity, four features are applied: 1) average pixel value; 2) standard deviation of pixel values; 3) standard correlation coefficient defined by the sector-form model; and 4) concentration feature determined from the density gradient. After employing the new method to 335 digitized mammograms, the detection sensitivity for the partial loss masses jumped from 70% to 90% when the number of false positives was kept constant (0.2/image). Moreover, a combination of the existing method and the new method improved the true-positive rate up to 97%. Such results indicate that the new technique may improve the performance of our computer-aided diagnosis system for mammographic masses effectively.

The purpose of this study is to develop a technique for computer-aided diagnosis (CAD) systems to detect lung nodules in helical X-ray pulmonary computed tomography CT) images. We propose a novel template-matching technique based on a genetic algorithm (GA) template matching (GATM) for detecting nodules existing within the lung area; the GA was used to determine the target position in the observed image efficiently and to select an adequate template image from several reference patterns for quick template matching. In addition, a conventional template matching was employed to detect nodules existing on the lung wall area, lung wall template matching (LWTM), where semicircular models were used as reference patterns; the semicircular models were rotated according to the angle of the target point on the contour of the lung wall. After initial detecting candidates using the two template-matching methods, we extracted a total of 13 feature values and used them to eliminate false-positive findings. Twenty clinical cases involving a total of 557 sectional images were used in this study. 71 nodules out of 98 were correctly detected by our scheme (i.e., a detection rate of about 72%), with the number of false positives at approximately 1.1/sectional image. Our present results show that our scheme can be regarded as a technique for CAD systems to detect nodules in helical CT pulmonary images.

The purpose of this study was to evaluate acoustic noise in echo planar imaging (EPI) at various magnetic resonance imaging (MRI) centers and to compare EPI acoustic noise with that in other fast pulse sequences. We measured A-weighted root-mean-square sound pressure levels and peak impulse sound pressure levels for EPI, under the same conditions, in eleven clinical super-conducting MRI systems. We also compared sound pressure levels for the EPI and six different pulse sequences and analyzed the acoustic noise spectra. Sound pressure levels during the use of the EPI differed greatly among institutions. Moreover, sound pressure levels of the EPI were not significantly different from those of other fast pulse sequences and were within permissible noise exposure levels. In comparison to other fast sequences, the EPI had significantly greater acoustic noise in the high-octave band frequency.

The authors developed a simple method for determining the presampling modulation transfer function (MTF). which includes the unsharpness of the detector and the effect of the sampling aperture, in digital radiographic (DR) systems. With this method, the presampling MTF is determined by the Fourier transform of a ;finely sampled' line spread function (LSF) obtained with a slightly angulated slit in a single exposure. Since the effective sampling distance becomes much smaller than the original sampling distance of the DR system, the effect of aliasing on the MTF calculations can be eliminated. The authors applied this method to the measurement of the presampling MTF of a compound radiographic system and examined the directional dependence, the effect of exponential extrapolation, and the effect of different sampling distances. It is shown that the technique of multiple slit exposure and exponential extrapolation of the LSF tail, which has been commonly used in analog seven-film systems, can be employed in DR systems. The authors determined the glare fraction in order to estimate the component of low-frequency drop mainly due to ;glare'