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Texture analysis in perfusion images of prostate cancer—A case study

Jacek Śmietański, Ryszard Tadeusiewicz, Elżbieta Łuczyńska
2010 International Journal of Applied Mathematics and Computer Science  
Texture analysis in perfusion images of prostate cancerA case study The analysis of prostate images is one of the most complex tasks in medical images interpretation.  ...  In this paper some methods of automatic analysis of prostate perfusion tomographic images are presented and discussed.  ...  Unauthenticated Download Date | 7/18/15 12:00 AM Texture analysis in perfusion images of prostate cancer-A case study Table 1. Coefficients of GLCM. 151 no. name abbr.  ... 
doi:10.2478/v10006-010-0011-9 fatcat:rtb723zoy5c6di5fcvfbiuep5m

EP-1876: An image-based method to quantify biomechanical properties of the rectum in RT of prostate cancer

O. Casares-Magaz, M. Thor, L. Donghua, J.B. Frøkjær, P. Kræmer, K. Krogh, A.M. Drewes, H. Gregersen, V. Moiseenko, M. Høyer, L.P. Muren
2016 Radiotherapy and Oncology  
Purpose or Objective: Patients suffering from high-grade gliomas currently have a median survival time of 14 months despite treatment.  ...  Our purpose was to investigate whether MR perfusion and relative Cerebral Blood Volume (rCBV) maps could predict tumor recurrence areas and improve treatment planning.  ...  In this study we present a magnetic resonance imaging (MRI) based method to quantitate the thickness and elasticity of the rectal wall in prostate cancer patients treated with RT.  ... 
doi:10.1016/s0167-8140(16)33127-9 fatcat:al3kkaoqvvei3aavaymyjcrkme

Unravelling tumour heterogeneity using next-generation imaging: radiomics, radiogenomics, and habitat imaging

E. Sala, E. Mema, Y. Himoto, H. Veeraraghavan, J.D. Brenton, A. Snyder, B. Weigelt, H.A. Vargas
2017 Clinical Radiology  
It reviews the potential value of radiomics and radiogenomics in assisting in the diagnosis of cancer disease and determining cancer aggressiveness.  ...  Lastly, it provides an overview of the obstacles in these emergent fields today including reproducibility, need for validation, imaging analysis standardisation, data sharing and clinical translatability  ...  The funding source had no involvement in the writing of the review and in the decision to submit the review for publication.  ... 
doi:10.1016/j.crad.2016.09.013 pmid:27742105 pmcid:PMC5503113 fatcat:br3rqmkcxnc7tikn33hs2sykyi

Multi-Image Texture Analysis in Classification of Prostatic Tissues from MRI. Preliminary Results [chapter]

Dorota Duda, Marek Kretowski, Romain Mathieu, Renaud de Crevoisier, Johanne Bezy-Wendling
2014 Advances in Intelligent Systems and Computing  
In the work, a (semi)automatic multi-image texture analysis is applied to the characterization of prostatic tissues from Magnetic Resonance Images (MRI).  ...  The method consists in a simultaneous analysis of several images, each acquired under dierent conditions, but representing the same part of the organ.  ...  This work was supported by the grant S/WI/2/2013 from Bialystok University of Technology.  ... 
doi:10.1007/978-3-319-06593-9_13 fatcat:ollou7oiirhylhhm3lji6tdgjm

CT-based Radiomics for Risk Stratification in Prostate Cancer

Sarah OS. Osman, Ralph TH. Leijenaar, Aidan J. Cole, Ciara A. Lyons, Alan R. Hounsell, Kevin M. Prise, Joe M. O'Sullivan, Philippe Lambin, Conor K. McGarry, Suneil Jain
2019 International Journal of Radiation Oncology, Biology, Physics  
To explore the role of Computed tomography (CT)-based radiomics features in prostate cancer risk stratification.  ...  . 1 Other than skin cancer, prostate cancer is also the most common cancer in males in the United States, with approximately 64,690 new cases per year. 2 Traditionally, prostate cancer is stratified  ...  An overall Introduction Prostate cancer is one of the most frequently diagnosed cancers globally; it is the most common cancer in males in the United Kingdom, with approximately 130 new cases per day  ... 
doi:10.1016/j.ijrobp.2019.06.2504 pmid:31254658 fatcat:v7tzsyx6prcjfmtgxxyatankfu

The expanding landscape of diffusion-weighted MRI in prostate cancer

Andreas G. Wibmer, Evis Sala, Hedvig Hricak, Hebert Alberto Vargas
2016 Abdominal Radiology  
The added value of diffusion-weighted magnetic resonance imaging (DW-MRI) for the detection, localization, and staging of primary prostate cancer has been extensively reported in original studies and meta-analyses  ...  A considerable proportion of slowgrowing, indolent cancers do not affect the patients' life expectancy, as repeatedly shown in the literature and recently summarized in a meta-analysis of autopsy-studies  ...  In another analysis, however, f and the perfusion-related diffusion coefficient (D*) were not significantly different in prostate cancer and benign prostatic hyperplasia [36] and further research will  ... 
doi:10.1007/s00261-016-0646-6 pmid:26814501 pmcid:PMC5458420 fatcat:zcdctu5rurcergxd3rgagqyty4

Editorial Comment: Advances in MRI and PET of the prostate: concurrence or complementarity?

Raphaële Renard-Penna, Mathieu Gauthé, Jean-Noël Talbot
2018 European Radiology  
A rapid survey of recent issues of European Radiology confirms the vitality of the clinical research in modern noninvasive imaging of prostate cancer.  ...  This Editorial Comment refers to the articles "Diagnostic evaluation of magnetization transfer and diffusion kurtosis imaging for prostate cancer detection in a re-biopsy population" by Barrett T et al  ...  In their study, Barrett et al. [4] evaluate two additional functional sequences, diffusion kurtosis imaging (DKI) and magnetisation transfer imaging (MTI) for prostate cancer detection.  ... 
doi:10.1007/s00330-018-5459-2 pmid:29858639 fatcat:n6pvtiy5rjgifoqg7cbn3g5nlq

"Textural analysis of multiparametric MRI detects transition zone prostate cancer"

Harbir S. Sidhu, Salvatore Benigno, Balaji Ganeshan, Nikos Dikaios, Edward W. Johnston, Clare Allen, Alex Kirkham, Ashley M. Groves, Hashim U. Ahmed, Mark Emberton, Stuart A. Taylor, Steve Halligan (+1 others)
2016 European Radiology  
. • TZ containing significant tumour reveals higher postcontrast T1-weighted homogeneity. • The utility of MR texture analysis in prostate cancer merits further investigation.  ...  Key Points • MR textural features of prostate transition zone may discriminate significant prostatic cancer. • Transition zone (TZ) containing significant tumour demonstrates a less peaked ADC histogram  ...  and processing of images for analysis in this study.  ... 
doi:10.1007/s00330-016-4579-9 pmid:27620864 pmcid:PMC5408048 fatcat:v4auocyjlfcozbkn2suewtwfby

Utility of T2-weighted MRI texture analysis in assessment of peripheral zone prostate cancer aggressiveness: a single-arm, multicenter study

Gabriel A. Nketiah, The PCa-MAP Consortium, Mattijs Elschot, Tom W. Scheenen, Marnix C. Maas, Tone F. Bathen, Kirsten M. Selnæs
2021 Scientific Reports  
This retrospective multicenter study evaluated the potential of T2W image-derived textural features for quantitative assessment of peripheral zone prostate cancer (PCa) aggressiveness.  ...  Texture analysis of T2W images provides quantitative information or features that are associated with peripheral zone PCa aggressiveness and can augment their classification.  ...  Although a number of promising studies have reported the utility of MRI texture analysis in prostate cancer [19] [20] [21] [22] [23] [36] [37] [38] , very few are based on multicenter cohorts 22 or focused  ... 
doi:10.1038/s41598-021-81272-x pmid:33483545 fatcat:oyh4voorn5d6vdjriamaw4bc2i

Texture analysis of medical images for radiotherapy applications

Elisa Scalco, Giovanna Rizzo
2017 British Journal of Radiology  
Review article: Texture analysis of medical image in radiotherapy BJR  ...  In this context, texture analysis, consisting of a variety of mathematical techniques that can describe the grey-level patterns of an image, plays an important role in assessing the spatial organization  ...  ACKNOWLEDGMENTS The authors thank the Radiology and Radiotherapy Department of Regina Elena National Cancer Institute, Rome, Italy; the Prostate Cancer Program of Fondazione IRCCS Istituto Nazionale dei  ... 
doi:10.1259/bjr.20160642 pmid:27885836 pmcid:PMC5685100 fatcat:2ko66us7wfg23lhia3dc74dcxi

Photoacoustic tomography of intact human prostates and vascular texture analysis identify prostate cancer biopsy targets

Brittani L. Bungart, Lu Lan, Pu Wang, Rui Li, Michael O. Koch, Liang Cheng, Timothy A. Masterson, Murat Dundar, Ji-Xin Cheng
2018 Photoacoustics  
In conclusion, 1064 nm PAT and US texture-based feature analysis provided successful prostate biopsy targets.  ...  A B S T R A C T Prostate cancer is poorly visualized on ultrasonography (US) so that current biopsy requires either a templated technique or guidance after fusion of US with magnetic resonance imaging.  ...  Conflict of interest statement The authors declare that there are no conflicts of interest. J-X. C., P.W., and R.L. have a financial interest in Vibronix, Inc., which did not support this work.  ... 
doi:10.1016/j.pacs.2018.07.006 pmid:30109195 pmcid:PMC6088561 fatcat:kvikmrdedvhvfh3vqn3tiwf4kq

Computer-aided diagnosis of prostate cancer with MRI

Baowei Fei
2017 Current Opinion in Biomedical Engineering  
Multi-parametric magnetic resonance imaging (mp-MRI) has an increasingly important role in the diagnosis of prostate cancer.  ...  This manuscript presents an overview of the literature regarding prostate CAD using mp-MRI, while focusing on the studies of the most recent five years.  ...  Quantitative analysis of multiparametric prostate MR images: differentiation between prostate cancer and normal tissue and correlation with Gleason score-a computer-aided diagnosis development study.  ... 
doi:10.1016/j.cobme.2017.09.009 pmid:29732440 pmcid:PMC5931723 fatcat:sul7nf3gu5cvteroyjk42rziee

More than Meets the Eye: Using Textural Analysis and Artificial Intelligence as Decision Support Tools in Prostate Cancer Diagnosis—A Systematic Review

Teodora Telecan, Iulia Andras, Nicolae Crisan, Lorin Giurgiu, Emanuel Darius Căta, Cosmin Caraiani, Andrei Lebovici, Bianca Boca, Zoltan Balint, Laura Diosan, Monica Lupsor-Platon
2022 Journal of Personalized Medicine  
", "textural analysis", "artificial intelligence", "computer assisted diagnosis", out of which 35 were included in the final review.  ...  (1) Introduction: Multiparametric magnetic resonance imaging (mpMRI) is the main imagistic tool employed to assess patients suspected of harboring prostate cancer (PCa), setting the indication for targeted  ...  Conflicts of Interest: The authors declare no conflict of interest.  ... 
doi:10.3390/jpm12060983 pmid:35743766 pmcid:PMC9225075 fatcat:i7hukvcxcjb6tdqxisbnhq75vm

Seeing the Complete Picture: Imaging in Prostate Cancer

Layla Southcombe
2020 European Medical Journal Urology  
and perfusion," both key hallmarks of cancerous tumours.  ...  outlined the use of MRI in PCa, highlighting that "MRI is an excellent tool to help us in finding the most relevant cancer in the prostate because we not only can look at anatomy, but also cell density  ...  he presented the case of "MRI is an excellent tool to help us in finding the most relevant cancer in the prostate because we not only can look at anatomy, but also cell density and perfusion" a male  ... 
doi:10.33590/emjurol/20f0903 fatcat:kmghulfwlzbpvkkvfyw7r6gyny

Prediction of Clinically Significant Cancer Using Radiomics Features of Pre-Biopsy of Multiparametric MRI in Men Suspected of Prostate Cancer

Chidozie N. Ogbonnaya, Xinyu Zhang, Basim S. O. Alsaedi, Norman Pratt, Yilong Zhang, Lisa Johnston, Ghulam Nabi
2021 Cancers  
Methods: This was a prospective study, recruiting 200 men suspected of having prostate cancer. Participants were imaged using a protocol-based 3T MRI in the pre-biopsy setting.  ...  Conclusion: Quantitative GLCM texture analyses of pre-biopsy MRI has the potential to be used as a non-invasive imaging technique to predict clinically significant cancer in men suspected of having prostate  ...  (A) mpMR images showing the segmented region of interest (ROI) marked red in both the T2WI and ADC images for extraction of quantitative imaging texture features (a,b).  ... 
doi:10.3390/cancers13246199 pmid:34944819 pmcid:PMC8699138 fatcat:ejabj7mzwrfbfo4odogbivbrs4
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