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Texture Feature Extraction and Analysis for Polyp Differentiation via Computed Tomography Colonography

Yifan Hu, Zhengrong Liang, Bowen Song, Hao Han, Perry J. Pickhardt, Wei Zhu, Chaijie Duan, Hao Zhang, Matthew A. Barish, Chris E. Lascarides
2016 IEEE Transactions on Medical Imaging  
Image textures in computed tomography colonography (CTC) have great potential for differentiating non-neoplastic from neoplastic polyps and thus can advance the current CTC  ...  Acknowledgments This work was partly supported by the NIH/NCI under grants #CA082402 and #CA143111.  ...  Index Terms Colorectal polyps; computed tomography colonography; texture feature; polyp subtype classification I.  ... 
doi:10.1109/tmi.2016.2518958 pmid:26800530 pmcid:PMC4891231 fatcat:7ly24tq7vbairoeq27dxtkrera

Volumetric texture features from higher-order images for diagnosis of colon lesions via CT colonography

Bowen Song, Guopeng Zhang, Hongbing Lu, Huafeng Wang, Wei Zhu, Perry J. Pickhardt, Zhengrong Liang
2014 International Journal of Computer Assisted Radiology and Surgery  
The gain in differentiation capability shall increase the potential of computed tomography colonography for colorectal cancer screening by not only detecting polyps but also classifying them for optimal  ...  Methods-Based on the Haralick texture analysis method, we introduce a virtual pathological model to explore the utility of texture features from high-order differentiations, i.e., gradient and Correspondence  ...  Lu is partially supported by the National Natural Science Foundation of China under Grant #81230035 and #81071220 and also the National Key Technologies R&D Program of China under Grant #2011BAI12B03.  ... 
doi:10.1007/s11548-014-0991-2 pmid:24696313 pmcid:PMC4185018 fatcat:itfa4gbhp5dhbn4xp3bhsnbr6e

Front Matter: Volume 10134

2017 Medical Imaging 2017: Computer-Aided Diagnosis  
Publication of record for individual papers is online in the SPIE Digital Library. SPIEDigitalLibrary.org Paper Numbering: Proceedings of SPIE follow an e-First publication model.  ...  Utilization of CIDs allows articles to be fully citable as soon as they are published online, and connects the same identifier to all online and print versions of the publication.  ...  classification of Barretts Esophagus through feature enhancement [10134-109] 10134 34 False positive reduction for wall thickness-based detection of colonic flat polyps via CT colonography [10134  ... 
doi:10.1117/12.2277119 dblp:conf/micad/X17 fatcat:ika7pheqxngdxejyvkss4dkbv4

Multi-scale characterizations of colon polyps via computed tomographic colonography

Weiguo Cao, Marc J. Pomeroy, Yongfeng Gao, Matthew A. Barish, Almas F. Abbasi, Perry J. Pickhardt, Zhengrong Liang
2019 Visual Computing for Industry, Biomedicine, and Art  
Texture features have played an essential role in the field of medical imaging for computer-aided diagnosis.  ...  This study aims to increase the potential of these features by introducing multi-scale analysis into the construction of GLCM texture descriptor.  ...  Kenneth Ng and Ms. Anushka Banerjee. Authors' contributions All authors discussed the major idea and the details of this article. They all read and approved the final manuscript.  ... 
doi:10.1186/s42492-019-0032-7 pmid:32240410 pmcid:PMC7099560 fatcat:zkyezyn77zbrhhuqh5x347v2lm

Colonic Polyp Detection in CT Colonography with Fuzzy Rule Based 3D Template Matching

Niyazi Kilic, Osman N. Ucan, Onur Osman
2008 Journal of medical systems  
In this paper, we introduced a computer aided detection (CAD) system to facilitate colonic polyp detection in computer tomography (CT) data using cellular neural network, genetic algorithm and three dimensional  ...  The CAD system is evaluated with 1043 CT colonography images from 16 patients containing 15 marked polyps. All colon regions are segmented properly.  ...  Virtual colonoscopy (VC) or Computed tomography colonography (CTC) is an emerging method for polyp detection through the entire colon.  ... 
doi:10.1007/s10916-008-9159-3 pmid:19238892 fatcat:uisjugow3vekhbky5teyukbqom

Polyp Detection and Segmentation from Video Capsule Endoscopy: A Review

V. Prasath
2016 Journal of Imaging  
We review different polyp detection approaches for VCE imagery and provide systematic analysis with challenges faced by standard image processing and computer vision methods.  ...  To analyze the large scale video data produced by VCE exams automatic image processing, computer vision, and learning algorithms are required.  ...  Polyp detection schemes applicable to colonoscopy and Computed Tomography (CT) colonography use mainly geometry based techniques (see, for example, [15] ).  ... 
doi:10.3390/jimaging3010001 fatcat:ifkngz7v7rceteeihh3vhpw5uy

Integration of 3D scale-based pseudo-enhancement correction and partial volume image segmentation for improving electronic colon cleansing in CT colonograpy

Hao Zhang, Lihong Li, Hongbin Zhu, Hao Han, Bowen Song, Zhengrong Liang
2014 Journal of X-Ray Science and Technology  
detection (CAD) of colon polyps (computer observer).  ...  Orally administered tagging agents are usually used in CT colonography (CTC) to differentiate residual bowel content from native colonic structures.  ...  The authors would also like to thank the anonymous reviewers for their constructive comments and suggestions that greatly improve the quality of the manuscript.  ... 
doi:10.3233/xst-140424 pmid:24699352 pmcid:PMC3979539 fatcat:s6qjks5caff65axkptaqctsmzu

Volume-based feature analysis of mucosa for automatic initial polyp detection in virtual colonoscopy

Su Wang, Hongbin Zhu, Hongbing Lu, Zhengrong Liang
2008 International Journal of Computer Assisted Radiology and Surgery  
In this paper, we present a volume-based mucosa-based polyp candidate determination scheme for automatic polyp detection in computed colonography.  ...  In doing so, polyp candidates are optimally determined by computing and clustering these fast marching-based adaptive geometrical features.  ...  Acknowledgments This work was partly supported by NIH Grant #CA082402 and #CA120917 of the National Cancer Institute. H.  ... 
doi:10.1007/s11548-008-0215-8 pmid:19774204 pmcid:PMC2747332 fatcat:jd4zean6qjehrgbbtf5v5tahjy

Real-time Surface Analysis and Tagged Material Cleansing for Virtual Colonoscopy [article]

Christoph Russ, Christoph Kubisch, Feng Qiu, Wei Hong, Patric Ljung
2010 International Workshop on Volume Graphics, Proceedings of the  
We show how to convert a standard mono-resolution representation into a out-of-core multiresolution structure, both for labeled and continuous scalar volumes.  ...  This representation has little overhead over storing precomputed gradients, and has the advantage that feature planes provide minimal geometric information about the underlying volume regions that can  ...  Approximately 70 million computed tomography (CT) scans are performed annually [dGMK * 09], which underlines the use of volumetric imaging in medical applications and creates a need for advanced rendering  ... 
doi:10.2312/vg/vg10/029-036 fatcat:kjchpz6ehneahjpd4ogvnu4pmu

Lesion classification by model-based feature extraction: A differential affine invariant model of soft tissue elasticity [article]

Weiguo Cao, Marc J. Pomeroy, Zhengrong Liang, Yongfeng Gao, Yongyi Shi, Jiaxing Tan, Fangfang Han, Jing Wang, Jianhua Ma, Hongbin Lu, Almas F. Abbasi, Perry J. Pickhardt
2022 arXiv   pre-print
This paper proposes an alternative approach of modeling the elasticity using Computed Tomography (CT) imaging modality for model-based feature extraction machine learning (ML) differentiation of lesions  ...  The model-based elastic image features are extracted from the feature maps and fed to machine learning to perform lesion classifications.  ...  Acknowledgments This work was partially supported by the NIH/NCI grant #CA206171 and #CA220004.  ... 
arXiv:2205.14029v1 fatcat:72tap6idejckxi46xbdyxfvkli

Automated Polyp Detection in Colon Capsule Endoscopy

Alexander V. Mamonov, Isabel N. Figueiredo, Pedro N. Figueiredo, Yen-Hsi Richard Tsai
2014 IEEE Transactions on Medical Imaging  
The algorithm acts as a binary classifier, which labels the frame as either containing polyps or not, based on the geometrical analysis and the texture content of the frame.  ...  The features extracted by the segmentation procedure are classified according to an assumption that the polyps are characterized as protrusions that are mostly round in shape.  ...  ACKNOWLEDGMENTS The authors thank the anonymous referees for valuable comments and suggestions that helped to improve the manuscript.  ... 
doi:10.1109/tmi.2014.2314959 pmid:24710829 fatcat:4b2uimrbcfbv7glumqyk6l4e5m

Coarse-to-fine classification via parametric and nonparametric models for computer-aided diagnosis

Le Lu, Meizhu Liu, Xiaojing Ye, Shipeng Yu, Heng Huang
2011 Proceedings of the 20th ACM international conference on Information and knowledge management - CIKM '11  
Classification is one of the core problems in Computer-Aided Diagnosis (CAD), targeting for early cancer detection using 3D medical imaging interpretation.  ...  These two steps can also be considered as effective "sample pruning" and "feature pursuing + kNN/template matching", respectively.  ...  Image interpretation based cancer detection via 3D computer tomography has emerged as a common clinical practice, and many computer-aided detection tools for enhancing radiologists' diagnostic performance  ... 
doi:10.1145/2063576.2064004 dblp:conf/cikm/LuLYYH11 fatcat:74nsydvy7vbyxbk3kaoejjgjoi

Virtual colonoscopy versus optical colonoscopy

Zhengrong Liang, Robert J Richards
2010 Expert Opinion in Medical Diagnostics  
A strategy that utilizes VC for population-based screening over the age of 50 and OC for screening high-risk individuals and those with positive VC findings would result in a significantly reduced rate  ...  Utilizing a strategy of virtual colonoscopy (VC) in asymptomatic patients over 50, with optical colonoscopy (OC) follow-up for removal of detected adenomatous polyps may result in lowering the colon cancer  ...  In other words, the extraction of the colon wall volume via the ECC innovation [90] and the analysis of texture features from image intensity of the wall [95] would be the key steps toward computer-aided  ... 
doi:10.1517/17530051003658736 pmid:20473367 pmcid:PMC2869208 fatcat:2z5izc6n3zcjfewxx2e6ki6a3a

Advancements in Oncology with Artificial Intelligence—A Review Article

Nikitha Vobugari, Vikranth Raja, Udhav Sethi, Kejal Gandhi, Kishore Raja, Salim R. Surani
2022 Cancers  
The current detection and screening methods for colon polyps and breast cancer have a vast amount of data, so they are ideal areas for studying the global standardization of artificial intelligence.  ...  ML offers the prospect of unraveling undiscovered features from routinely acquired neuroimaging for improving treatment planning, prognostication, monitoring, and response assessment of CNS tumors such  ...  CT colonography differentiation by texture analysis based on gradient and curvature of high-order images and random forest models significantly improved the accuracy of the classification of CPs [70,  ... 
doi:10.3390/cancers14051349 pmid:35267657 pmcid:PMC8909088 fatcat:f6wf7jmiqvarhhlmuwy7nt5444

Machine learning and radiology

Shijun Wang, Ronald M. Summers
2012 Medical Image Analysis  
We focused on six categories of applications in radiology: medical image segmentation, registration, computer aided detection and diagnosis, brain function or activity analysis and neurological disease  ...  diagnosis from fMR images, content-based image retrieval systems for CT or MRI images, and text analysis of radiology reports using natural language processing (NLP) and natural language understanding  ...  Acknowledgments We thank Andrew Dwyer, MD, for critical review of the manuscript. This manuscript was support by the Intramural Research Program of the National Institutes of Health Clinical Center.  ... 
doi:10.1016/j.media.2012.02.005 pmid:22465077 pmcid:PMC3372692 fatcat:4ynexgzdhrev7dfqapmjpxexuu
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