Multi-resolution Active Models for Image Segmentation

Image segmentation refers to the process of subdividing an image into a set of non-overlapping regions. Image segmentation is a critical and essential step to almost all higher level image processing and pattern recognition approaches, where a good segmentation relieves higher level applications from considering irrelevant and noise data in the image. Image segmentation is also considered as the most challenging image processing step due to several reasons including spatial discontinuity of the region of interest and the absence of a universally accepted criteria for image segmentation. Among the huge number of segmentation approaches, active contour models or simply snakes receive a great attention in the literature. Where the contour/boundary of the region of interest is defined as the set of pixels at which the active contour reaches its equilibrium state. In general, two forces control the movement of the snake inside the image, internal force that prevents the snake from stretching and bending and external force that pulls the snake towards the desired object boundaries. One main limitation of active contour models is their sensitivity to image noise. Specifically, noise sensitivity leads the active contour to fail to properly converge, getting caught on spurious image features, preventing the iterative solver from taking large steps towards the final contour. Additionally, active contour initialization forms another type of limitation. Where, especially in noisy images, the active contour needs to be initialized relatively close to the object of interest, otherwise the active contour will be pulled by other non-real/spurious image features. This dissertation, aiming to improve the active model-based segmentation, introduces two models for building up the external force of the active contour. The first model builds up a scale-based-weighted gradient map from all resolutions of the undecimated wavelet transform, with preference given to coarse gradients over fine gradients. The undecimated wavelet transform, due to its near shift-invariance and the absence of down-sampling properties, produces well-localized gradient maps at all resolutions of the transform. Hence, the proposed final weighted gradient map is able to better drive the snake towards its final equilibrium state. Unlike other multiscale active contour algorithms that define a snake at each level of the hierarchy, our model defines a single snake with the external force field is simultaneously built based on gradient maps from all scales. The second model proposes the incorporation of the directional information, revealed by the dual tree complex wavelet transform (DT CWT), into the external force field of the active contour. At each resolution of the transform, a steerable set of convolution kernels is created and used for external force generation. In the proposed model, the size and the orientation of the kernels depend on the scale of the DT CWT and the local orientation statistics of each pixel. Experimental results using nature, synthetic and Optical Coherent Tomography (OCT) images reflect the superiority of the proposed models over the classical and the state-of-the-art models

Impact of Training Images on Radiometric Compensation

The increasing availability of both high-resolution projectors andimperfect displays make radiometric correction an essential componentin all modern projection systems. Particularly, projectingin casual locations, such as classrooms, open areas and homes,calls for the development of radiometric correction techniques thatare fully automatic and deal with display imperfections in real-time.This paper reviews the current radiometric compensation algorithmsand discusses the influence of different training images on theirperformance

Understanding Blur and Model Learning in Projector Compensation

Radiometric compensation enables data projectors to use texturedsurfaces such as automobiles, building and theater stages as pro-jection screens, accomplished by modelling the reflectance char-acteristic of the surface and inverting it to find the compensationfunction. In this paper, we explore the effects of point spread func-tion / blur of the projector on the performance of existing radiometriccompensation algorithms. Two changes to the existing model areproposed which help to consider projector blur in model learning.Proposed changes can be combined with any radiometric com-pensation strategy to improve its perceptual performance withoutincreasing the computational complexity

Determining arterial blood velocity using MAUI software from recorded doppler ultrasound videos

Objectives: The purpose of this study was to investigate the repeatability and reproducibility of a new software, developed to provide measurements of arterial blood velocity from recorded Doppler ultrasound videos. Methods: The “Measurements from Arterial Ultrasound Imaging” (MAUI) software (Hedgehog Medical Inc.), developed for the measurement of arterial dimensions, has been expanded to measure the blood velocity from ultrasound videos. MAUI uses an adaptive based segmentation and intelligent outlier removal image analysis method to determine the instantaneous peak velocity in the positive and negative directions and the intensity weighted mean of the signal. Three recorded videos of popliteal arterial velocity were used to evaluate the reproducibility and repeatability of MAUI. For this assessment, two investigators (E1 and E2) each performed 10 measurements of the three test videos using MAUI. Results: MAUI provided blood velocity measurements (cm/s) for each frame of each video. The ten measurements made by E1 and E2 were averaged and are listed below (mean ± SD).Video # Velocity Measure E1 E21 Positive Envelope 27.84 ± 0.15 27.31 ± 0.28 Negative Envelope -13.99 ± 0.28 -13.68 ± 0.19 Mean Signal 13.80 ± 0.24 13.81 ± 0.102 Positive Envelope 42.30 ± 0.13 42.34 ± 0.33 Negative Envelope -11.51 ± 0.28 -11.53 ± 0.24 Mean Signal 29.69 ± 0.02 29.08 ± 0.363 Positive Envelope 53.48 ± 0.11 53.54 ± 0.20 Negative Envelope -13.66 ± 0.10 -13.40 ± 0.21 Mean Signal 38.60 ± 0.12 38.47 ± 0.17Conclusion: Preliminary assessments suggest that MAUI is a viable method for the measurement of blood velocity from recorded Doppler ultrasound video with high repeatability and low interrater variability. In future, measurements of velocity may be combined with existing continuous measurements of arterial diameter for the calculation of blood flow and assessments of vascular health and disease.<br/

Motion Detection in High Resolution Enhancement

Shifted Superposition (SSPOS) is a resolution enhancement methodwhere apparent high-resolution content is displayed using a lowresolutionprojection system with an opto-mechanical shifter. WhileSSPOS-enhanced projectors have been showing promising resultsin still images, they still suffer from motion artifacts in video contents.Motivated by this, we present a novel approach to apparentprojector resolution enhancement for videos via motion-basedblurring module. We propose the use of a motion detection moduleand a blurring module to compensate for both SSPOS-resulted andnatural motion artifacts in the video content. To accomplish this,we combine both local and global motion estimation algorithms togenerate accurate dense flow fields. The detected motion regionsare enhanced using directional Gaussian filters. Preliminary resultsshow that the proposed method can produce accurate densemotion vectors and significantly reduce the artifacts in videos

Active Contours for Measuring Arterial Wall Diameter of Astronauts from Ultrasound Images

The non-invasive assessment of cardiovascular changes with spaceflightoften involves the measurement of blood vessel dimensionusing ultrasound imaging. However, many commonly used measurementtechniques are often manually intensive and dependenton the individual making the measurements. We propose a newautomated method for measuring the vessel dimensions which involvescreating a smoothed edge map of the image and using activecontours to converge to the upper and lower vessel boundaries.Preliminary results show that we are able to use this methodto detect vessels walls for vascular measurements from ultrasoundimages

Improved OCT Human Corneal segmentation Using Bayesian Residual Transform

The inherent poor signal to noise ratio of Optical Coherent Tomography(OCT) is considered as a main limitation of OCT segmentation,particularly because images are sampled quickly, at high resolutions,and in-vivo. Furthermore, speckle noise is generated bythe reflections of the OCT LASER limits the ability of automaticallysegmenting OCT images. This paper presents a novel method toautomatically segment human corneal OCT images. The proposedmethod uses Bayesian Residual Transform (BRT) to build a noiserobust external force map, that guides active contours model to thecorneal data in OCT images. Experimental results show that theproposed method outperforms the classical as well as the state-ofthe-art methods

Seroprevalence of camel brucellosis in Qatar

Brucellosis is a significant zoonotic disease and one of the most common neglected diseases worldwide. It can infect a wide range of domestic and wild animal species. Infected animals are usually culled, causing substantial economic losses to animal owners and the country’s economy in general. The disease is endemic among cattle, sheep, and goats in many countries around the Middle East and prevalent in most Gulf Cooperation Council countries, comprising a significant public health risk in the region. This study investigated the seroprevalence of brucellosis among camels in Qatar. Two hundred and forty-eight samples were collected from dromedary camels from 28 farms across the entire country. Each sample was tested for Brucella antibodies with both Rose Bengal and competitive enzyme-linked immunosorbent assay. Only samples that tested positive by both tests were considered seropositive for brucellosis. The overall prevalence was (20.6%, 95% CI, 15.7–26.1). The association between sex and seropositivity was slightly significant (Χ2 = 4.32, P = 0.04), with higher seroprevalence in females. Camels below breeding age (i.e., < 4 years old) showed decreased seropositivity (3.4%, 95% CI, 0.1–17.8), compared to (22.8%, 95% CI, 17.4–29.0) seropositivity in camels ≥ 4 years of age, with a significant association between age groups and seropositivity (P = 0.02). Our results indicate that the seroprevalence of brucellosis in Qatar’s camels is alarming, mandating more efforts to control the disease. The findings of this study will aid in selecting better effective measures to control camel brucellosis in Qatar. Further studies need to be conducted on Brucella infection among camels to determine the predisposing risk factors and the steps that should be followed to control brucellosis.Open Access funding provided by the Qatar National Library. This work was supported by Qatar University grant number QUCG-BRC-20/21–2 and high potential projects program QPH3P-BRC-2021–604 to Nahla O. Eltai