Dr. Wei-Min Liu Profile

Dr. Wei-Min Liu

Assistant Professor

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Publications (9)

Proceedings Article | 1 April 2008 Paper

Automated discovery of meniscal tears on MR imaging: a novel high-performance computer-aided detection application for radiologists

Bharath Ramakrishna, Nabile Safdar, Khan Siddiqui, Woojin Kim, Weimin Liu, Ganesh Saiprasad, Chein-I Chang, Eliot Siegel

Proceedings Volume 6915, 691531 (2008) https://doi.org/10.1117/12.773167

KEYWORDS: CAD systems, Computer aided diagnosis and therapy, Magnetic resonance imaging, Injuries, Diagnostics, Imaging systems, Image processing, Computer aided design, Computing systems

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Proceedings Article | 24 March 2008 Paper

Comparing agreement measures

Wei-min Liu, Brandon Gallas

Proceedings Volume 6917, 69170D (2008) https://doi.org/10.1117/12.773037

KEYWORDS: Binary data, Monte Carlo methods, Receivers, Computer simulations, Statistical analysis, Medical imaging, Gold, Electrical engineering, Imaging systems, Silver

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Proceedings Article | 7 May 2007 Paper

A comparative study and analysis between vertex component analysis and orthogonal subspace projection for endmember extraction

Chao-Cheng Wu, Weimin Liu, Hsuan Ren, Chein-I Chang

Proceedings Volume 6565, 656523 (2007) https://doi.org/10.1117/12.719555

KEYWORDS: Algorithm development, Minerals, Detection and tracking algorithms, Principal component analysis, Independent component analysis, Target detection, Signal to noise ratio, Calcite, Reflectivity, Remote sensing

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Proceedings Article | 7 May 2007 Paper

An orthogonal subspace projection-based for estimation of virtual dimensionality for hyperspectral data exploitation

Weimin Liu, Chao-Cheng Wu, Chein-I Chang

Proceedings Volume 6565, 65651A (2007) https://doi.org/10.1117/12.719543

KEYWORDS: Detection and tracking algorithms, Minerals, Interference (communication), Error analysis, Data modeling, Signal processing, Signal detection, Signal to noise ratio, Independent component analysis, Array processing

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Proceedings Article | 30 March 2007 Paper

Automatic CAD of meniscal tears on MR imaging: a morphology-based approach

Bharath Ramakrishna, Weimin Liu, Nabile Safdar, Khan Siddiqui, Woojin Kim, Krishna Juluru, Chein-I Chang, Eliot Siegel

Proceedings Volume 6514, 651437 (2007) https://doi.org/10.1117/12.713288

KEYWORDS: Computer aided diagnosis and therapy, Image segmentation, Magnetic resonance imaging, Image processing, Cartilage, Image processing algorithms and systems, Surgery, Detection and tracking algorithms, Binary data, Tissues

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Proceedings Article | 25 October 2006 Paper

Exploration of methods for estimation of number of endmembers in hyperspectral imagery

Chao-Cheng Wu, Weimin Liu, Chein-I Chang

Proceedings Volume 6378, 63781C (2006) https://doi.org/10.1117/12.684912

KEYWORDS: Hyperspectral imaging, Minerals, Image analysis, Interference (communication), Detection theory, Signal to noise ratio, Image sensors, Calcite, Neodymium, Signal detection

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Proceedings Article | 4 May 2006 Paper

Sample spectral correlation-based measures for subpixels and mixed pixels in real hyperspectral imagery

Weimin Liu, Chein-I Chang

Proceedings Volume 6233, 62330J (2006) https://doi.org/10.1117/12.665285

KEYWORDS: Hyperspectral imaging, Sensors, Image processing, Distance measurement, Error analysis, Databases, Algorithm development, Roads, Image sensors, Image classification

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Proceedings Article | 5 November 2005 Paper

3D ROC analysis for detection software used in water monitoring

Wei-min Liu, Su Wang, Chein-I Chang, Janet Jensen, James Jensen, Harlan Knapp, Robert Daniel, Ray Yin

Proceedings Volume 5995, 59950A (2005) https://doi.org/10.1117/12.626611

KEYWORDS: Signal detection, Sensors, Software development, Binary data, Signal processing, Detector development, Target detection, Image classification, Chemical analysis, Medical diagnostics

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Under the U.S. Army sponsored Joint Service Agent Water Monitor (JSAWM) program, developing hand-held assays using tickets for chemical/biological agent detection has been of major interest. One of keys to success is to develop detection algorithms that not only can effectively detect the presence of various agents, but also can quantify the detected agents. This paper presents a recent development of detection software that can perform 3-dimensional (3D) receiver operating characteristics (ROC) analysis which is based on quantified agent concentration. The ROC curves have been widely used in communications, signal processing and medical communities to evaluate the effectiveness of a detection technique. It generally formulates a signal detection problem as a binary composite hypothesis testing problem with the null hypothesis and the alternative hypothesis represents the case of no signal and the case of signal presence respectively. The ROC curve is then plotted based on the detection probability (power) P_D versus the false alarm probability, P_F. Unfortunately, such a two-dimensional (2D) (P_D,P_F)-based ROC curve does not factor in the concentration detected in an agent signal which is a crucial parameter in chemical/biological agent detection. The proposed 3D ROC analysis is developed from such a need. It includes an additional parameter, referred to as threshold t, which is used to threshold the detected agent signal concentration. Consequently, a different value of t results in a different 2D ROC curve. In order to take into account the thresholding factor t, a 3D ROC curve is derived and plotted based on three parameters, (P_D,P_F,t). As a result of the 3D ROC curve, three 2D ROC curves can be also derived. One is the conventional 2D (P_D,P_F)-ROC curve. Another is a 2D (P_D,t)-ROC curve which describes the relationship between P_D and the threshold value t. A third one is a 2D (P_F,t)-ROC curve which shows the effect of the threshold value t on P_F. The utility of the proposed 3D ROC analysis will be demonstrated by the detection software developed by the UMBC for the tickets used in HHA for water monitoring.

Proceedings Article | 14 December 2004 Paper

Morphological algorithms for processing tickets by handheld assay

Mingkai Hsueh, Antonio Plaza, Jing Wang, Su Wang, Wei-min Liu, Hsuan Ren, Chein Chang, Janet Jensen, James Jensen, Matthew Odom, Ryen Hydutsky, Harlan Knapp, Ray Yin

Proceedings Volume 5584, (2004) https://doi.org/10.1117/12.571968

KEYWORDS: Algorithm development, Image processing, Image segmentation, Chemical analysis, Biological research, Biological detection systems, Biological weapons, Mathematical morphology, Scanners, Detection and tracking algorithms

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