Prof. Lihong C. Li Profile

Prof. Lihong C. Li

SPIE Involvement:

Author

Area of Expertise:

Signal / image processing , Computer aided detection / diagnosis , Pattern recognition , Image segmentation , Medical informatics , Computer vision

Publications (47)

SPIE Journal Paper | 9 July 2024

Examining feature extraction and classification modules in machine learning for diagnosis of low-dose computed tomographic screening-detected in vivo lesions

Daniel Liang, David Liang, Marc J. Pomeroy, Yongfeng Gao, Licheng Kuo, Lihong Li

JMI, Vol. 11, Issue 04, 044501, (July 2024) https://doi.org/10.1117/12.10.1117/1.JMI.11.4.044501

KEYWORDS: Feature extraction, Image classification, Computed tomography, Tissues, Polyps, Machine learning, In vivo imaging, X-ray computed tomography, Medical imaging, Computer aided detection

Read Abstract +

PurposeMedical imaging-based machine learning (ML) for computer-aided diagnosis of in vivo lesions consists of two basic components or modules of (i) feature extraction from non-invasively acquired medical images and (ii) feature classification for prediction of malignancy of lesions detected or localized in the medical images. This study investigates their individual performances for diagnosis of low-dose computed tomography (CT) screening-detected lesions of pulmonary nodules and colorectal polyps.ApproachThree feature extraction methods were investigated. One uses the mathematical descriptor of gray-level co-occurrence image texture measure to extract the Haralick image texture features (HFs). One uses the convolutional neural network (CNN) architecture to extract deep learning (DL) image abstractive features (DFs). The third one uses the interactions between lesion tissues and X-ray energy of CT to extract tissue-energy specific characteristic features (TFs). All the above three categories of extracted features were classified by the random forest (RF) classifier with comparison to the DL-CNN method, which reads the images, extracts the DFs, and classifies the DFs in an end-to-end manner. The ML diagnosis of lesions or prediction of lesion malignancy was measured by the area under the receiver operating characteristic curve (AUC). Three lesion image datasets were used. The lesions’ tissue pathological reports were used as the learning labels.ResultsExperiments on the three datasets produced AUC values of 0.724 to 0.878 for the HFs, 0.652 to 0.965 for the DFs, and 0.985 to 0.996 for the TFs, compared to the DL-CNN of 0.694 to 0.964. These experimental outcomes indicate that the RF classifier performed comparably to the DL-CNN classification module and the extraction of tissue-energy specific characteristic features dramatically improved AUC value.ConclusionsThe feature extraction module is more important than the feature classification module. Extraction of tissue-energy specific characteristic features is more important than extraction of image abstractive and characteristic features.

Proceedings Article | 3 April 2024 Presentation + Paper

An investigation on the individual performance of feature extraction and classification modules in machine learning for diagnosis of low-dose computed tomography screening-detected lesions

Daniel Liang, David Liang, Marc Pomeroy, Yongfeng Gao, Lihong Li, Licheng Kuo

Proceedings Volume 12927, 129271L (2024) https://doi.org/10.1117/12.3006622

KEYWORDS: Feature extraction, Computed tomography, Polyps, Image classification, Tissues, Machine learning, X-ray computed tomography, Deep learning, Computer aided detection, Random forests

Read Abstract +

Proceedings Article | 7 April 2023 Poster + Paper

Using virtual monoenergetic images in Karhunen–Loève domain to differentiate lesion pathology

Yongfeng Gao, Shaojie Chang, Marc Pomeroy, Lihong Li, Zhengrong Liang

Proceedings Volume 12465, 124652R (2023) https://doi.org/10.1117/12.2654390

KEYWORDS: Pathology, Polyps, Lung, Colon, X-ray computed tomography, 3D modeling, Image classification

Read Abstract +

Proceedings Article | 4 April 2022 Poster + Presentation + Paper

Multi-channel medical image segmentation method in Hessian domain

Shuheng Cao, Ethan Yu, Aidan Clarke, Yongfeng Gao, Lihong Li

Proceedings Volume 12033, 1203333 (2022) https://doi.org/10.1117/12.2612659

KEYWORDS: Image segmentation, Medical imaging, Kidney, Breast, Brain, Tissues, Colon, Lung, Magnetic resonance imaging, Information technology

Read Abstract +

Proceedings Article | 16 March 2020 Presentation + Paper

A multi-stage fusion strategy for multi-scale GLCM-CNN model in differentiating malignant from benign polyps

Jiaxing Tan, Shu Zhang, Weiguo Cao, Yongfeng Gao, Lihong Li, Yumei Huo, Zhengrong Liang

Proceedings Volume 11314, 113141S (2020) https://doi.org/10.1117/12.2549831

KEYWORDS: Tumor growth modeling, Feature extraction, Convolution, Visualization, Curium, Computer aided diagnosis and therapy, Visual process modeling, Colorectal cancer, Performance modeling, Tumors

Read Abstract +

Proceedings Article | 15 March 2019 Paper

Sharpness preserved sinogram synthesis using convolutional neural network for sparse-view CT imaging

Jiaxing Tan, Yongfeng Gao, Yumei Huo, Lihong Li, Zhengrong Liang

Proceedings Volume 10949, 109490E (2019) https://doi.org/10.1117/12.2512894

KEYWORDS: Computed tomography, Convolutional neural networks, Performance modeling, Feature extraction, X-ray computed tomography, Visual process modeling, Convolution, Tissues, Sensors, Image restoration

Read Abstract +

Proceedings Article | 9 March 2018 Paper

A feasibility study of extracting tissue textures from a previous normal-dose CT database as prior for Bayesian reconstruction of current ultra-low-dose CT images

Yongfeng Gao, Zhengrong Liang, Yuxiang Xing, Hao Zhang, Jianhua Ma, Hongbing Lu, Lihong Li, Bo Chen, Marc Pomeroy, William Moore

Proceedings Volume 10573, 105733C (2018) https://doi.org/10.1117/12.2293854

KEYWORDS: Magnetorheological finishing, Tissues, X-ray computed tomography, Lung, Image segmentation, Databases, X-rays, Reconstruction algorithms, Computed tomography, CT reconstruction

Read Abstract +

Tremendous research efforts have been devoted to lower the X-ray radiation exposure to the patient in order to expand the utility of computed tomography (CT), particularly to pediatric imaging and population-based screening. When the exposure dosage goes down, both the X-ray quanta fluctuation and the system electronic background noise become significant factors affecting the image quality. Conventional edge-preserving noise smoothing would sacrifice tissue textures and compromise the clinical tasks. To relieve these challenges, this work models the noise problem by pre-log shifted Poisson statistics and extracts tissue textures from previous normal-dose CT scans as prior knowledge for texturepreserving Bayesian reconstruction of current ultralow-dose CT images. The pre-log shift Poisson model considers accurately both the X-ray quanta fluctuation and the system electronic noise while the prior knowledge of tissue textures removes the limitation of the conventional edge-preserving noise smoothing. The Bayesian reconstruction was tested by experimental studies. One patient chest scan was selected from a database of 133 patients’ scans at 100mAs/120kVp normal-dose level. From the selected patient scan, ultralow-dose data was simulated at 5mAs/120kVp level. The other 132 normal-dose scans were grouped according to how close their lung tissue texture patterns are from that of the selected patient scan. The tissue textures of each group were used to reconstruct the ultralow-dose scan by the Bayesian algorithm. The closest group to the selected patient produced almost identical results to the reconstruction when the tissue textures of the selected patient’s normal-dose scan were used, indicating the feasibility of extracting tissue textures from a previous normal-dose database to reconstruct any current ultralow-dose CT image. Since the Bayesian reconstruction can be time consuming, this work further investigates a strategy to efficiently store the projection matrix rather than computing the line integrals on-flight. This strategy accelerated the computing speed by more than 18 times.

Proceedings Article | 2 March 2018 Paper

A new medical image segmentation model based on fractional order differentiation and level set

Bo Chen, Shan Huang, Feifei Xie, Lihong Li, Wensheng Chen, Zhengrong Liang

Proceedings Volume 10574, 1057435 (2018) https://doi.org/10.1117/12.2292931

KEYWORDS: Image segmentation, Medical imaging, Magnetic resonance imaging, Fourier transforms, Heart, Computed tomography, Neuroimaging, Brain, Image enhancement, Visual process modeling

Read Abstract +

Proceedings Article | 27 February 2018 Presentation + Paper

A new fractional order derivative based active contour model for colon wall segmentation

Bo Chen, Lihong Li, Huafeng Wang, Xinzhou Wei, Shan Huang, Wensheng Chen, Zhengrong Liang

Proceedings Volume 10575, 1057517 (2018) https://doi.org/10.1117/12.2293677

KEYWORDS: Colon, Image segmentation, Solid modeling, Photovoltaics, Colorectal cancer, Computer aided diagnosis and therapy, Cancer, Expectation maximization algorithms, Image processing, Tomography

Read Abstract +

Proceedings Article | 3 March 2017 Paper

A study of oral contrast coating on the surface of polyps: an implication for computer-aided detection and classification of polyps

Harmanpreet Singh, Lihong Li, Marc Pomeroy, Perry Pickhardt, Matthew Barish, Donald Harrington, Zhengrong Liang

Proceedings Volume 10134, 101340I (2017) https://doi.org/10.1117/12.2254514

KEYWORDS: Endoscopy, 3D image processing, 3D vision, Barium, Translucency, Colon, Coating, Computer-aided diagnosis, Virtual colonoscopy, Computed tomography, Computer aided diagnosis and therapy

Read Abstract +

Proceedings Article | 3 March 2017 Paper

False positive reduction for wall thickness-based detection of colonic flat polyps via CT colonography

Marc Pomeroy, Lihong Li, Hao Han, Xinzhou Wei, Perry Pickhardt, Zhengrong Liang

Proceedings Volume 10134, 1013434 (2017) https://doi.org/10.1117/12.2254565

KEYWORDS: Colorectal cancer, Cancer, Feature selection, Colon, Feature extraction, Virtual colonoscopy, Computer aided diagnosis and therapy, Computer aided design, Computer-aided diagnosis, Volume rendering, Statistical analysis, Image classification, Computed tomography

Read Abstract +

Proceedings Article | 3 March 2017 Paper

A new framework for detection of initial flat polyp candidates based on a dual level set competition model

Huafeng Wang, Lihong Li, Xinzhou Wei, Wanquan Liu, Yuehai Wang, Zhengrong Liang

Proceedings Volume 10134, 1013435 (2017) https://doi.org/10.1117/12.2254600

KEYWORDS: Colon, Computer-aided diagnosis, Image segmentation, Computer aided design, Virtual colonoscopy, Computer aided diagnosis and therapy, Colorectal cancer, Expectation maximization algorithms

Read Abstract +

Proceedings Article | 30 March 2016 Paper

Texture-preserving Bayesian image reconstruction for low-dose CT

Hao Zhang, Hao Han, Yifan Hu, Yan Liu, Jianhua Ma, Lihong Li, William Moore, Zhengrong Liang

Proceedings Volume 9783, 97834I (2016) https://doi.org/10.1117/12.2217297

KEYWORDS: CT reconstruction, X-ray computed tomography, Lung, Colon, X-ray imaging, X-rays, Tissues, Reconstruction algorithms, Bone, Computed tomography

Read Abstract +

Proceedings Article | 24 March 2016 Paper

An integrated classifier for computer-aided diagnosis of colorectal polyps based on random forest and location index strategies

Yifan Hu, Hao Han, Wei Zhu, Lihong Li, Perry Pickhardt, Zhengrong Liang

Proceedings Volume 9785, 97851L (2016) https://doi.org/10.1117/12.2216353

KEYWORDS: Computer aided diagnosis and therapy, Feature selection, 3D modeling, Image classification, Computer-aided diagnosis, Computed tomography, Probability theory, Error control coding, Cancer, Receivers, Colorectal cancer, Feature extraction

Read Abstract +

Proceedings Article | 20 March 2015 Paper

Detection of colonic polyp candidates with level set-based thickness mapping over the colon wall

Hao Han, Lihong Li, Chaijie Duan, Yang Zhao, Huafeng Wang, Zhengrong Liang

Proceedings Volume 9414, 94141F (2015) https://doi.org/10.1117/12.2082415

KEYWORDS: Colon, Image segmentation, Computer aided diagnosis and therapy, 3D modeling, Photovoltaics, Virtual colonoscopy, Tissues, Visualization, 3D image processing

Read Abstract +

Proceedings Article | 18 March 2015 Paper

Adaptive nonlocal means-based regularization for statistical image reconstruction of low-dose X-ray CT

Hao Zhang, Jianhua Ma, Jing Wang, Yan Liu, Hao Han, Lihong Li, William Moore, Zhengrong Liang

Proceedings Volume 9412, 94123K (2015) https://doi.org/10.1117/12.2082244

KEYWORDS: Image filtering, X-ray computed tomography, Image restoration, X-rays, X-ray imaging, Data acquisition, CT reconstruction, Computed tomography, Scanners, Denoising

Read Abstract +

Proceedings Article | 24 March 2014 Paper

An adaptive approach to centerline extraction for CT colonography using MAP-EM segmentation and distance field

Hao Peng, Lihong Li, Huafeng Wang, Hao Han, Perry Pickhardt, Zhengrong Liang

Proceedings Volume 9035, 903510 (2014) https://doi.org/10.1117/12.2043956

KEYWORDS: Colon, Intestine, Image segmentation, Expectation maximization algorithms, Photovoltaics, Tissues, Image processing algorithms and systems, Virtual colonoscopy, Tomography, Algorithm development

Read Abstract +

Proceedings Article | 20 March 2014 Paper

Automated polyp measurement based on colon structure decomposition for CT colonography

Huafeng Wang, Lihong Li, Hao Han, Hao Peng, Bowen Song, Xinzhou Wei, Zhengrong Liang

Proceedings Volume 9035, 90350B (2014) https://doi.org/10.1117/12.2043648

KEYWORDS: Colon, Expectation maximization algorithms, Computer aided diagnosis and therapy, Colorectal cancer, Virtual colonoscopy, Computed tomography, 3D modeling, Volume rendering, Detection and tracking algorithms, Cancer

Read Abstract +

Proceedings Article | 19 March 2014 Paper

Nonlocal means-based regularizations for statistical CT reconstruction

Hao Zhang, Jianhua Ma, Yan Liu, Hao Han, Lihong Li, Jing Wang, Zhengrong Liang

Proceedings Volume 9033, 903337 (2014) https://doi.org/10.1117/12.2043949

KEYWORDS: CT reconstruction, Reconstruction algorithms, Data modeling, Image quality, Denoising, Image filtering, Computed tomography, Image resolution, X-rays, Control systems

Read Abstract +

Proceedings Article | 18 March 2014 Paper

A novel colonic polyp volume segmentation method for computer tomographic colonography

Huafeng Wang, Lihong Li, Hao Han, Bowen Song, Hao Peng, Yunhong Wang, Lihua Wang, Zhengrong Liang

Proceedings Volume 9035, 90352W (2014) https://doi.org/10.1117/12.2043556

KEYWORDS: Image segmentation, Colon, Computer aided diagnosis and therapy, Volume rendering, Tomography, Colorectal cancer, Cancer, Environmental sensing, Tissues, Medical imaging

Read Abstract +

Proceedings Article | 18 March 2014 Paper

A novel computer-aided detection system for pulmonary nodule identification in CT images

Hao Han, Lihong Li, Huafeng Wang, Hao Zhang, William Moore, Zhengrong Liang

Proceedings Volume 9035, 90352D (2014) https://doi.org/10.1117/12.2043964

KEYWORDS: Lung, Computer aided diagnosis and therapy, 3D image processing, Computed tomography, Image segmentation, Chest, Databases, Feature extraction, Lung cancer

Read Abstract +

Proceedings Article | 6 March 2013 Paper

A comparison study of sinogram- and image-domain penalized re-weighted least-squares approaches to noise reduction for low-dose cone-beam CT

Hao Zhang, Yan Liu, Hao Han, Jing Wang, Jianhua Ma, Lihong Li, Zhengrong Liang

Proceedings Volume 8668, 86683E (2013) https://doi.org/10.1117/12.2007111

KEYWORDS: Image restoration, Reconstruction algorithms, X-ray computed tomography, Denoising, X-rays, 3D image reconstruction, Image resolution, Image quality, CT reconstruction, Head

Read Abstract +

Reducing X-ray exposure to the patients is one of the major research efforts in the computed tomography (CT) field, and one of the common strategies to achieve it is to lower the mAs setting (by lowering the X-ray tube current and/or shortening the exposure time) in currently available CT scanners. However, the image quality from low mAs acquisition is severely degraded due to excessive quantum noise, if no adequate noise control is applied during image reconstruction. Different from filter-based algorithms, statistical reconstruction algorithms model the statistical property of the noise using a cost function and minimize the cost function for an optimal solution in statistical sense. The algorithms have shown to be feasible and effective in both sinogram and image domain. In our previous researches, we proposed penalized reweighted least-squares (PRWLS) approaches to sinogram noise reduction and image reconstruction for low-dose CT imaging, which are in this statistical category. This work is a continuation of the research along this direction and aims to compare the reconstruction quality of two different PRWLS implementations for low-dose cone-beam CT reconstruction: (1) PRWLS sinogram restoration followed by analytical Feldkamp-Davis- Kress reconstruction, (2) fully iterative PRWLS image reconstruction. Inspired by our recent study on the variance of low-mAs projection data in presence of electric noise background, a more accurate weight was adopted in the weighted least-squares term. An anisotropic quadratic form penalty was utilized in both PRWLS implementations to preserve edges during noise reduction. Experiments using the CatPhan® 600 phantom and anthropomorphic head phantom were carried to study the relevant performance of these two implementations on image reconstruction. The results revealed that the implementation (2) can outperform implementation (1) in terms of noise-resolution tradeoff measurement and analysis of the reconstructed small objects due to its matched image edge-preserved penalty in the image domain. However, those gains are offset by the cost of increased computational time. Thus, further examination of real patient data is necessary to show the clinical significance of the iterative PRWLS image reconstruction over the PRWLS sinogram restoration.

Proceedings Article | 28 February 2013 Paper

A shape constrained MAP-EM algorithm for colorectal segmentation

Huafeng Wang, Lihong Li, Bowen Song, Fangfang Han, Zhengrong Liang

Proceedings Volume 8670, 86702F (2013) https://doi.org/10.1117/12.2008138

KEYWORDS: Image segmentation, Expectation maximization algorithms, Colon, Tissues, Computer aided diagnosis and therapy, Computed tomography, Colorectal cancer, Image processing algorithms and systems, Medical imaging, Solid modeling

Read Abstract +

Proceedings Article | 3 March 2012 Paper

Variance estimation of x-ray CT sinogram in radon domain

Jianhua Ma, Zhengrong Liang, Yi Fan, Yan Liu, Jing Huang, Lihong Li, Wufan Chen, Hongbing Lu

Proceedings Volume 8313, 83132G (2012) https://doi.org/10.1117/12.911669

KEYWORDS: Sensors, X-ray computed tomography, X-rays, Interference (communication), Radon, Statistical analysis, Signal detection, Image quality, Scanners, Image restoration

Read Abstract +

Proceedings Article | 23 February 2012 Paper

Automatic colonic fold segmentation for computed tomography colonography

Hongbin Zhu, Matthew Barish, Lihong Li, Bowen Song, Donald Harrington, Perry Pickhardt, Zhengrong Liang

Proceedings Volume 8315, 83150X (2012) https://doi.org/10.1117/12.911336

KEYWORDS: Colon, Image segmentation, Image processing algorithms and systems, Synthetic aperture radar, Computed tomography, Solids, Tomography, Solid modeling, Image registration, Image restoration

Read Abstract +

Proceedings Article | 23 February 2012 Paper

An integrated electronic colon cleansing for CT colonoscopy via MAP-EM segmentation and scale-based scatter correction

Hao Zhang, Lihong Li, Hongbin Zhu, Qin Lin, Donald Harrington, Zhengrong Liang

Proceedings Volume 8315, 83151L (2012) https://doi.org/10.1117/12.910922

KEYWORDS: Tissues, Image segmentation, Colon, Thulium, Image processing algorithms and systems, Photovoltaics, Virtual colonoscopy, Computed tomography, Statistical analysis, Signal attenuation

Read Abstract +

Proceedings Article | 9 March 2011 Paper

Automatic teniae coli detection for computed tomography colonography

Hongbin Zhu, Lihong Li, Yi Fan, Qin Lin, Hongbing Lu, Xianfeng Gu, Zhengrong Liang

Proceedings Volume 7963, 79632N (2011) https://doi.org/10.1117/12.878059

KEYWORDS: Technetium, Colon, Solids, Principal component analysis, Computed tomography, Virtual colonoscopy, Databases, Image registration, Tomography, 3D image processing

Read Abstract +

Proceedings Article | 8 September 2010 Paper

Multispectral MRI-based virtual cystoscopy

Lihong Li, Hongbin Zhu, Su Wang, Xinzhou Wei, Zhengrong Liang

Proceedings Volume 7798, 77980C (2010) https://doi.org/10.1117/12.861448

KEYWORDS: Bladder, Image segmentation, Magnetic resonance imaging, Tissues, Virtual colonoscopy, Computer aided diagnosis and therapy, Expectation maximization algorithms, Photovoltaics, Tumors, Bladder cancer

Read Abstract +

Proceedings Article | 12 March 2008 Paper

Segmentation of multispectral bladder MR images with inhomogeneity correction for virtual cystoscopy

Lihong Li, Zhengrong Liang, Su Wang, Hongyu Lu, Xinzhou Wei, Mark Wagshul, Marlene Zawin, Erica Posniak, Christopher Lee

Proceedings Volume 6916, 69160U (2008) https://doi.org/10.1117/12.769914

KEYWORDS: Bladder, Image segmentation, Magnetic resonance imaging, Tissues, Virtual cystoscopy, Photovoltaics, Tumors, Multispectral imaging, Expectation maximization algorithms, Virtual colonoscopy

Read Abstract +

Proceedings Article | 29 March 2007 Paper

Gain by mixture-based image segmentation for virtual colonoscopy with colonic material tagging

Lihong Li, Su Wang, Zigang Wang, Jing Wang, Hongbing Lu, Zhengrong Liang

Proceedings Volume 6511, 65110V (2007) https://doi.org/10.1117/12.708927

KEYWORDS: Image segmentation, Tissues, Expectation maximization algorithms, Photovoltaics, Colon, Image processing algorithms and systems, Bone, Virtual colonoscopy, Algorithm development, Computed tomography

Read Abstract +

Proceedings Article | 29 March 2007 Paper

A new electronic colon cleansing method for virtual colonoscopy

Lihong Li, Su Wang, Jing Wang, Daria Eremina, Xinzhou Wei, Zhengrong Liang

Proceedings Volume 6511, 65112J (2007) https://doi.org/10.1117/12.710242

KEYWORDS: Colon, Virtual colonoscopy, Expectation maximization algorithms, Computed tomography, Tissues, Bone, Model-based design, Colorectal cancer, Statistical methods, Cancer

Read Abstract +

Proceedings Article | 13 March 2006 Paper

Quantitative analysis of multiple sclerosis: a feasibility study

Lihong Li, Xiang Li, Xinzhou Wei, Deborah Sturm, Hongbing Lu, Zhengrong Liang

Proceedings Volume 6143, 61430U (2006) https://doi.org/10.1117/12.654181

KEYWORDS: Image segmentation, Brain, Tissues, Magnetic resonance imaging, Photovoltaics, Neuroimaging, Quantitative analysis, Data modeling, Image analysis, 3D acquisition

Read Abstract +

Proceedings Article | 14 April 2005 Paper

A feasibility study on laxative-free bowel preparation for virtual colonoscopy

Zhengrong Liang, Dongqing Chen, Mark Wax, Sarang Lakare, Lihong Li, Joseph Anderson, Arie Kaufman, Donald Harrington

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.597357

KEYWORDS: Colon, Computed tomography, Virtual colonoscopy, 3D modeling, Image acquisition, Image segmentation, Endoscopy, Liquids, 3D image processing, Image resolution

Read Abstract +

Proceedings Article | 14 April 2005 Paper

A pilot study on less-stressful bowel preparation for virtual colonoscopy screening with follow-up biopsy by optical colonoscopy

Zhengrong Liang, Sarang Lakare, Mark Wax, Dongqing Chen, Lihong Li, Joseph Anderson, Arie Kaufman, Donald Harrington

Proceedings Volume 5746, (2005) https://doi.org/10.1117/12.597437

KEYWORDS: Virtual colonoscopy, Colon, Computed tomography, Image segmentation, Biopsy, Magnesium, 3D modeling, Tablets, Barium, Image processing algorithms and systems

Read Abstract +

Proceedings Article | 12 May 2004 Paper

Computer-aided detection and diagnosis of colon polyps with morphological and texture features

Zigang Wang, Lihong Li, Joseph Anderson, Donald Harrington, Zhengrong Liang

Proceedings Volume 5370, (2004) https://doi.org/10.1117/12.535664

KEYWORDS: Colon, Tissues, Computer aided diagnosis and therapy, Computer aided design, Feature extraction, Virtual colonoscopy, Computed tomography, Image segmentation, Solid modeling

Read Abstract +

Proceedings Article | 30 April 2004 Paper

A new partial volume segmentation approach to extract bladder wall for computer-aided detection in virtual cystoscopy

Lihong Li, Zigang Wang, Xiang Li, Xinzhou Wei, Howard Adler, Wei Huang, Syed Rizvi, Hong Meng, Donald Harrington, Zhengrong Liang

Proceedings Volume 5369, (2004) https://doi.org/10.1117/12.535913

KEYWORDS: Bladder, Tissues, Magnetic resonance imaging, Image segmentation, Computer aided diagnosis and therapy, Multispectral imaging, Virtual cystoscopy, Photovoltaics, Computed tomography, 3D image processing

Read Abstract +

Proceedings Article | 5 June 2003 Paper

Adaptive noise reduction toward low-dose computed tomography

Hongbing Lu, Xiang Li, Lihong Li, Dongqing Chen, Yuxiang Xing, Jiang Hsieh, Zhengrong Liang

Proceedings Volume 5030, (2003) https://doi.org/10.1117/12.480374

KEYWORDS: Image filtering, Computed tomography, Signal to noise ratio, Digital filtering, Denoising, X-ray computed tomography, Nonlinear filtering, Smoothing, Gaussian filters, Image restoration

Read Abstract +

Proceedings Article | 15 May 2003 Paper

Inhomogeneity correction for magnetic resonance images with fuzzy C-mean algorithm

Xiang Li, Lihong Li, Hongbing Lu, Dongqing Chen, Zengrong Liang

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481375

KEYWORDS: Image segmentation, Magnetic resonance imaging, Fuzzy logic, Brain, Image processing algorithms and systems, Computer simulations, 3D image processing, Magnetism, Neuroimaging, Tissues

Read Abstract +

Proceedings Article | 15 May 2003 Paper

Skeleton-based 3D computer-aided detection of colonic polyps

Zigang Wang, Lihong Li, Xiang Li, Zhengrong Liang, Donald Harrington

Proceedings Volume 5032, (2003) https://doi.org/10.1117/12.481915

KEYWORDS: Colon, Image segmentation, Tissues, Computer aided diagnosis and therapy, Spherical lenses, Computed tomography, Expectation maximization algorithms, Virtual colonoscopy, Computer aided design, Convolution

Read Abstract +

Proceedings Article | 2 May 2003 Paper

Robust colon residue detection using vector-quantization-based classification for virtual colonoscopy

Sarang Lakare, Dongqing Chen, Lihong Li, Arie Kaufman, Mark Wax, Zhengrong Liang

Proceedings Volume 5031, (2003) https://doi.org/10.1117/12.480410

KEYWORDS: Colon, Virtual colonoscopy, Quantization, Computed tomography, Tissues, Image segmentation, 3D modeling, Colorectal cancer, 3D image processing, Cancer

Read Abstract +

Proceedings Article | 24 April 2002 Paper

Electronic colon cleansing using segmentation rays for virtual colonoscopy

Sarang Lakare, Dongqing Chen, Lihong Li, Arie Kaufman, Zhengrong Liang

Proceedings Volume 4683, (2002) https://doi.org/10.1117/12.463608

KEYWORDS: Colon, Image segmentation, Virtual colonoscopy, Computed tomography, Cancer, Abdomen, Tissues, Colorectal cancer, Bone, Reconstruction algorithms

Read Abstract +

Proceedings Article | 24 April 2002 Paper

Image segmentation approach to extract colon lumen through colonic material tagging and hidden Markov random field model for virtual colonoscopy

Lihong Li, Dongqing Chen, Sarang Lakare, Kevin Kreeger, Ingmar Bitter, Arie Kaufman, Mark Wax, Petar Djuric, Zhengrong Liang

Proceedings Volume 4683, (2002) https://doi.org/10.1117/12.463607

KEYWORDS: Colon, Image segmentation, Expectation maximization algorithms, Virtual colonoscopy, Computed tomography, Tissues, Magnetorheological finishing, Colorectal cancer, Medical imaging, Tumor growth modeling

Read Abstract +

Proceedings Article | 3 July 2001 Paper

Segmentation of brain MR images: a self-adaptive online vector quantization approach

Lihong Li, Dongqing Chen, Hongbing Lu, Zhengrong Liang

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.431024

KEYWORDS: Image segmentation, Magnetic resonance imaging, Brain, Quantization, Image processing algorithms and systems, Neuroimaging, Data modeling, Tissues, Principal component analysis, Feature extraction

Read Abstract +

Proceedings Article | 3 July 2001 Paper

Combined transformation of ordering SPECT sinograms for signal extraction from measurements with Poisson noise

Hongbing Lu, Dongqing Chen, Lihong Li, Guoping Han, Zhengrong Liang

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.430968

KEYWORDS: Signal to noise ratio, Interference (communication), Single photon emission computed tomography, Electronic filtering, Digital filtering, Image filtering, Filtering (signal processing), Denoising, Data modeling, Smoothing

Read Abstract +

Proceedings Article | 3 July 2001 Paper

Renormalization method for inhomogeneity correction of MR images

Dongqing Chen, Lihong Li, Daeki Yoon, J. Lee, Zhengrong Liang

Proceedings Volume 4322, (2001) https://doi.org/10.1117/12.430967

KEYWORDS: Magnetic resonance imaging, Neck, Tissues, Magnetism, Neuroimaging, Brain, Algorithms, Scanners, Roentgenium, Filtering (signal processing)

Read Abstract +

Proceedings Article | 28 June 2001 Paper

3D distance-weighted Wiener filter for Poisson noise reduction in sinogram space for SPECT imaging

Hongbing Lu, Jui-His Cheng, Guoping Han, Lihong Li, Zhengrong Liang

Proceedings Volume 4320, (2001) https://doi.org/10.1117/12.430936

KEYWORDS: Filtering (signal processing), Electronic filtering, Single photon emission computed tomography, Signal attenuation, Signal to noise ratio, Denoising, Image filtering, Interference (communication), 3D image processing, Linear filtering

Read Abstract +

Proceedings Article | 21 May 2001 Paper

New method for quantitative analysis of multiple scelerosis using MR images

Dongqing Chen, Wei Huang, C. Christodoulou, Lihong Li, Huayuan Qian, Lauren Krupp, Zhengrong Liang

Proceedings Volume 4321, (2001) https://doi.org/10.1117/12.428160

KEYWORDS: Image segmentation, Brain, Magnetic resonance imaging, Tissues, Neuroimaging, Quantitative analysis, Image processing algorithms and systems, 3D image processing, Image registration, 3D metrology

Read Abstract +

Showing 5 of 47 publications

View contact details

UPDATE YOUR PROFILE

Is this your profile? Update it now.

Sign into your SPIE.org account

Don’t have a profile and want one?

Create an account on SPIE.org

Keywords/Phrases

Search In:

Publication Years