Rabab Ward | University of British Columbia (original) (raw)

Papers by Rabab Ward

Magnetic Resonance Imaging, 2012

SENSitivity Encoding (SENSE) is a mathematically optimal parallel MRI technique when the coil sen... more SENSitivity Encoding (SENSE) is a mathematically optimal parallel MRI technique when the coil sensitivities are known. In recent times, Compressed Sensing (CS) based techniques are incorporated within the SENSE reconstruction framework to recover the underlying MR image. CS based techniques exploit the fact that the MR images are sparse in a transform domain (e.g. wavelets). Mathematically this leads to an l 1 -norm regularized SENSE reconstruction.

Recent Advances in Face Recognition, 2008

Publisher InTech

1999 IEEE International Conference on Acoustics, Speech, and Signal Processing. Proceedings. ICASSP99 (Cat. No.99CH36258), 1999

The very end of every chromosome is a region called the telomere. Telomeres are nucleo-protein co... more The very end of every chromosome is a region called the telomere. Telomeres are nucleo-protein complexes containing specific DNA repeat sequences whose lengths are strongly believed to give indications to aging and tumor progression. In order to study the role these repeat sequences play in the cell, we developed a fluorescence microscopy imaging system and associated image analysis methods to accurately measure these telomere lengths. To visualize the image of the tiny telomeres, we captured 2 spectrally different images of the same cell. One image contains only telomeres and the other contains only chromosomes. We next apply successful and novel methods to segment the telomere and chromosome images and then to link each chromosome with its telomeres. Our system is so far the only existing system available for this purpose and has already been in use in many research laboratories in Westem Europe, North America, and Hong Kong.

IEEE Signal Processing Magazine, 2016

2012 9th IEEE International Symposium on Biomedical Imaging (ISBI), 2012

ABSTRACT This work presents a fully automated approach to the quantification of the expression of... more ABSTRACT This work presents a fully automated approach to the quantification of the expression of antibodies in immunohistochemically stained tissue sections. Conventional RGB imaging was compared to multispectral imaging in the analysis of membrane stained tissue sections with high complexity, i.e. clustered and overlapping cells, and co-localization of stains. Preliminary results on more than 1700 cells suggest that multi-spectral imaging outperforms RGB imaging, particularly in complex and hard to segment regions.

In this paper we present a new method for extracting the fe- tal electrocardiogram (FECG) signal ... more In this paper we present a new method for extracting the fe- tal electrocardiogram (FECG) signal from one thoracic ECG signal and one or more abdominal signals. Our method is based on the use of an adaptive Volterra filter (AVF) that is capable of synthesizing the nonlinear relation between the mother thoracic ECG signal and the abdominal signals which contains

International journal of computer assisted radiology and surgery, Jan 10, 2016

Image models are central to all image processing tasks. The great advancements in digital image p... more Image models are central to all image processing tasks. The great advancements in digital image processing would not have been made possible without powerful models which, themselves, have evolved over time. In the past decade, "patch-based" models have emerged as one of the most effective models for natural images. Patch-based methods have outperformed other competing methods in many image processing tasks. These developments have come at a time when greater availability of powerful computational resources and growing concerns over the health risks of the ionizing radiation encourage research on image processing algorithms for computed tomography (CT). The goal of this paper is to explain the principles of patch-based methods and to review some of their recent applications in CT. We first review the central concepts in patch-based image processing and explain some of the state-of-the-art algorithms, with a focus on aspects that are more relevant to CT. Then, we review som...

Sensors (Basel, Switzerland), 2016

This paper proposes a compressive sensing (CS) method for multi-channel electroencephalogram (EEG... more This paper proposes a compressive sensing (CS) method for multi-channel electroencephalogram (EEG) signals in Wireless Body Area Network (WBAN) applications, where the battery life of sensors is limited. For the single EEG channel case, known as the single measurement vector (SMV) problem, the Block Sparse Bayesian Learning-BO (BSBL-BO) method has been shown to yield good results. This method exploits the block sparsity and the intra-correlation (i.e., the linear dependency) within the measurement vector of a single channel. For the multichannel case, known as the multi-measurement vector (MMV) problem, the Spatio-Temporal Sparse Bayesian Learning (STSBL-EM) method has been proposed. This method learns the joint correlation structure in the multichannel signals by whitening the model in the temporal and the spatial domains. Our proposed method represents the multi-channels signal data as a vector that is constructed in a specific way, so that it has a better block sparsity structure...

2015 IEEE International Conference on Image Processing (ICIP), 2015

2015 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 2015

Conference proceedings : ... Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual Conference, 2008

The Common Spatial Patterns (CSP) algorithm finds spatial filters that are useful in discriminati... more The Common Spatial Patterns (CSP) algorithm finds spatial filters that are useful in discriminating different classes of electroencephalogram (EEG) signals such as those corresponding to different types of motor activities. This algorithm is however, sensitive to outliers because it involves the estimation of covariance matrices. Classical sample covariance estimates are easily affected even if a single outlier exists. To improve the CSP algorithm's robustness against outliers, this paper first investigates how multivariate outliers affect the performance of the CSP algorithm. We then propose a modified version of the algorithm whereby the classical covariance estimates are replaced by the robust covariance estimates obtained using Minimum Covariance Determinant (MCD) estimator. Median Absolute Deviation (MAD) is also used to robustly estimate the variance of the projected EEG signals. The results show that the proposed algorithm is able to reduce the influence of the outliers. ...

2010 IEEE International Conference on Image Processing, 2010

... Ehsan Nezhadarya, Z. Jane Wang and Rabab K. Ward ... 5020, pp. 95106, SPIE. [7] Asifullah Kh... more ... Ehsan Nezhadarya, Z. Jane Wang and Rabab K. Ward ... 5020, pp. 95106, SPIE. [7] Asifullah Khan and Anwar M. Mirza, Genetic perceptual shaping: Utilizing cover image and conceivable attack infor-mation during watermark embedding, Information Fusion, vol. 8, no. 4, pp. ...

Sensors, 2014

The use of wireless body sensor networks is gaining popularity in monitoring and communicating in... more The use of wireless body sensor networks is gaining popularity in monitoring and communicating information about a person's health. In such applications, the amount of data transmitted by the sensor node should be minimized. This is because the energy available in these battery powered sensors is limited. In this paper, we study the wireless transmission of electroencephalogram (EEG) signals. We propose the use of a compressed sensing (CS) framework to efficiently compress these signals at the sensor node. Our framework exploits both the temporal correlation within EEG signals and the spatial correlations amongst the EEG channels. We show that our framework is up to eight times more energy efficient than the typical wavelet compression method in terms of compression and encoding computations and wireless transmission. We also show that for a fixed compression ratio, our method achieves a better reconstruction quality than the CS-based state-of-the art method. We finally demonstrate that our method is robust to measurement noise and to packet loss and that it is applicable to a wide range of EEG signal types.

IEEE Transactions on Information Forensics and Security, 2000

We propose a robust quantization-based image watermarking scheme, called the gradient direction w... more We propose a robust quantization-based image watermarking scheme, called the gradient direction watermarking (GDWM), based on the uniform quantization of the direction of gradient vectors. In GDWM, the watermark bits are embedded by quantizing the angles of significant gradient vectors at multiple wavelet scales. The proposed scheme has the following advantages: 1) increased invisibility of the embedded watermark because the watermark is embedded in significant gradient vectors, 2) robustness to amplitude scaling attacks because the watermark is embedded in the angles of the gradient vectors, and 3) increased watermarking capacity as the scheme uses multiple-scale embedding. The gradient vector at a pixel is expressed in terms of the discrete wavelet transform (DWT) coefficients. To quantize the gradient direction, the DWT coefficients are modified based on the derived relationship between the changes in the coefficients and the change in the gradient direction. Experimental results show that the proposed GDWM outperforms other watermarking methods and is robust to a wide range of attacks, e.g., Gaussian filtering, amplitude scaling, median filtering, sharpening, JPEG compression, Gaussian noise, salt & pepper noise, and scaling.

CCECE 2003 - Canadian Conference on Electrical and Computer Engineering. Toward a Caring and Humane Technology (Cat. No.03CH37436), 2000

ABSTRACT A novel method, that selectively enhances the Visually im-portant regions in scalable H.... more ABSTRACT A novel method, that selectively enhances the Visually im-portant regions in scalable H.264 video encoding, is pro-posed. The proposed method is extremely fast and is de-signed to be used in rea-time video communications sys-tems. The method is based on Fine ...

Proceedings of 2010 Ieee International Symposium on Circuits and Systems, 2010

We present an efficient H.264/AVC block-size partitioning prediction method, which is based on ou... more We present an efficient H.264/AVC block-size partitioning prediction method, which is based on our proposed empirical rate and distortion models. Compared to other state-of-the-art transcoding methods, and for the same rate-distortion performance, our proposed algorithm requires the least computational complexity, reaching a 73% reduction in variable block-size motion estimation for SDTV sequences, and 71% reduction for CIF sequences.

Acoustics Speech and Signal Processing 1988 Icassp 88 1988 International Conference on, Mar 14, 2010

Page 1. A ROBUST MORPHOLOGICAL GRADIENT ESTIMATOR AND EDGE DETECTOR FOR COLOR IMAGES Ehsan Nezhad... more Page 1. A ROBUST MORPHOLOGICAL GRADIENT ESTIMATOR AND EDGE DETECTOR FOR COLOR IMAGES Ehsan Nezhadarya and Rabab K. Ward ... fH = H1(f1, f2,..., f5) = e arg max i,j ei,j (10) where ei,j is given by ei,j = fi − fj , i, j ∈{F−Rs} (11) ...