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...
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...
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. ...
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 ...
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) ...
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...
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...
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. ...
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 ...
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) ...
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