Dr. Sheikh K. Alam Profile

Dr. Sheikh K. Alam

at Riverside Research

SPIE Involvement:

Author

Publications (9)

SPIE Journal Paper | 22 June 2023

Texture quantified from ultrasound Nakagami parametric images is diagnostically relevant for breast tumor characterization

Sabiq Muhtadi, Rezwana R. Razzaque, Ahmad Chowdhury, Brian S. Garra, S. Kaisar Alam

JMI, Vol. 10, Issue S2, S22410, (June 2023) https://doi.org/10.1117/12.10.1117/1.JMI.10.S2.S22410

KEYWORDS: Tumors, Windows, Ultrasonography, Breast, Image classification, Feature extraction, Cooccurrence matrices, Spatial resolution, Tissues, MATLAB

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Proceedings Article | 25 February 2012 Paper

Modulus reconstruction from prostate ultrasound images using finite element modeling

Zhennan Yan, Shaoting Zhang, S. Kaisar Alam, Dimitris Metaxas, Brian Garra, Ernest Feleppa

Proceedings Volume 8320, 832016 (2012) https://doi.org/10.1117/12.911088

KEYWORDS: Prostate, Tumors, Finite element methods, Tissues, Elastography, Ultrasonography, 3D modeling, Natural surfaces, Inverse problems, Prostate cancer

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Proceedings Article | 12 April 2005 Paper

Prostate elastography: preliminary in vivo results

S. Alam, E. Feleppa, A. Kalisz, S. Ramchandran, R. Ennis, Frederick Lizzi, C.-S. Wuu, Jeffrey Ketterling

Proceedings Volume 5750, (2005) https://doi.org/10.1117/12.596788

KEYWORDS: Prostate, Elastography, Prostate cancer, Biopsy, Tissues, Cancer, Data acquisition, In vivo imaging, Ultrasonography, Scanners

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Proceedings Article | 23 May 2003 Paper

Variable uniform stretching strain estimator for elastography

Sheikh Alam

Proceedings Volume 5035, (2003) https://doi.org/10.1117/12.479956

KEYWORDS: Elastography, Tissues, Image quality, Data acquisition, Ultrasonography, Finite element methods, Computer simulations, Ultrasonics, Image segmentation, Signal processing

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We describe a novel and robust strain estimation method, which is capable of fast, accurate strain estimation even in the presence of large signal decorrelation. Global temporal stretching of post-compression signals compensating for the applied strain significantly improves the "quality" of strain estimates. In a natural extension of this approach (adaptive stretching), a search is performed at each data window for the stretch factor that maximizes the correlation between the pre- and post-compression echo signal segments. Adaptive stretching performs well under harsh signal environments (because the correlation is maximized at each location); however it is computation intensive because many iterations may be required at each location. In contrast, global stretching is a fast algorithm, but performs well only in areas where local strains are close to the applied strain. The proposed method strikes a balance between the speed of global stretching and the performance of adaptive stretching. In this method, global stretching is performed with a range of different stretch factors and strain maps are computed for each stretch factor. The correlation between the pre- and post-compression echo segments is the maximum when the stretch factor corresponds to the local strain. Thus, the area in each computed strain image with strain values closely corresponding to the uniform stretch factor will contain "good quality" strain estimates. (Naturally, this area is different in each image.) To produce a single elastogram at the end, these strain maps are combined as follows. Correlation values quantify the "quality" of strain estimates; thus, at each location we identify the strain map with the maximum correlation, and the strain value in that strain map at that location is chosen for the combined map. Results from data generated by finite-element simulation and phantom experiments show that the variable stretching strain estimator is fast and is significantly less susceptible to signal degradation than conventional strain estimators.

Proceedings Article | 11 April 2002 Paper

Computer-aided diagnosis of breast lesions using a multifeature analysis procedure

Sheikh Alam, Frederick Lizzi, Ernest Feleppa, Tian Liu, Andrew Kalisz

Proceedings Volume 4687, (2002) https://doi.org/10.1117/12.462165

KEYWORDS: Breast, Fractal analysis, Acoustics, Tissues, Signal attenuation, Tumors, Ultrasonography, Calibration, Data acquisition, Cancer

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Proceedings Article | 11 April 2002 Paper

Novel methods of analyzing radio-frequency echo signals for the purpose of imaging brachytherapy seeds used to treat prostate cancer

Ernest Feleppa, Sarayu Ramachandran, Sheikh Alam, Andrew Kalisz, J. Ketterling, Ronald Ennis, Cheng-Shie Wuu

Proceedings Volume 4687, (2002) https://doi.org/10.1117/12.462146

KEYWORDS: Prostate, Ultrasonography, Transducers, Tissues, Liver, Signal analyzers, Prostate cancer, Doppler effect, Computed tomography, Data acquisition

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Proceedings Article | 11 April 2002 Paper

Correlation-tracking strain estimator for elastography

Sheikh Alam, Sarayu Ramachandran, Frederick Lizzi

Proceedings Volume 4687, (2002) https://doi.org/10.1117/12.462153

KEYWORDS: Tissues, Correlation function, Elastography, Motion estimation, Finite element methods, Image compression, Transducers, Statistical analysis, Ultrasonography, Cancer

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Proceedings Article | 30 May 2001 Paper

Novel estimators for elastography

Sheikh Alam, Frederick Lizzi, Ernest Feleppa, T. Varghese

Proceedings Volume 4325, (2001) https://doi.org/10.1117/12.428207

KEYWORDS: Tissues, Elastography, Motion estimation, Error analysis, Finite element methods, Transducers, Ultrasonography, Ultrasonics, Signal processing, Signal to noise ratio

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Proceedings Article | 12 April 2000 Paper

Ultrasonic multifeature analysis procedures for breast lesion classification

Sheikh Alam, Frederick Lizzi, Ernest Feleppa, Tian Liu, Andrew Kalisz

Proceedings Volume 3982, (2000) https://doi.org/10.1117/12.382226

KEYWORDS: Tissues, Signal attenuation, Breast, Tumors, Ultrasonics, Data acquisition, Analytical research, Spectrum analysis, Statistical analysis, Image segmentation

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Showing 5 of 9 publications

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