NDLI: Non-parametric Bayesian estimation of apparent diffusion coefficient from diffusion-weighted magnetic resonance imaging data

Content Provider	IEEE Xplore Digital Library
Author	Cameron, A. Glaister, J. Wong, A. Haider, M.A.
Copyright Year	2012
Description	Author affiliation: Dept. of Syst. Design Eng., Univ. of Waterloo, Waterloo, ON, Canada (Cameron, A.; Glaister, J.; Wong, A.) \|\| Dept. of Med. Imaging, Univ. of Toronto, Toronto, ON, Canada (Haider, M.A.)
Abstract	A promising approach to prostate cancer diagnosis is multi-parametric MRI. One of the key modalities used in multi-parametric MRI is diffusion weighted MRI. Using multiple diffusion weighted MR acquisitions taken with different magnetic gradient strengths, the apparent diffusion coefficient (ADC) is calculated and can be used to identify tumors in the prostate. Current algorithms used to calculate ADC assume a parametric measurement model, but this assumption is not true due to the presence of additional phenomena during the acquisition process. A novel Non-parametric Estimated ADC (NEstA) algorithm is proposed which uses a Monte Carlo strategy to learn the inherent measurement distribution model based on the underlying statistical behavior of the DWI measurements to estimate the ADC values. The proposed algorithm is compared to the results of the commonly used least-squares (LS) estimation algorithm for computing ADC values. Nine test patient cases with visible tumors in the prostate gland were processed using both algorithms and compared visually. It was found that NEstA produced ADC data with reduced artifacts while preserving structure. Quantitatively, Fisher's criterion measuring the separability of the healthy prostate and tumor tissues was computed for the nine patient cases, comparing the NEstA and LS methods. It was found that Fisher's criterion increased with the NEstA method, meaning the separation of classes was more pronounced.
Sponsorship	IEEE Eng. Medicine Biol. Soc.
Starting Page	412
Ending Page	415
File Size	441910
Page Count	4
File Format	PDF
ISBN	9781424441198
ISSN	1557170X
e-ISBN	9781457717871
DOI	10.1109/EMBC.2012.6345955
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2012-08-28
Publisher Place	USA
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Magnetic resonance imaging Tumors Estimation Prostate cancer Pollution measurement Bayesian methods
Content Type	Text
Resource Type	Article
Subject	Signal Processing Biomedical Engineering Health Informatics Computer Vision and Pattern Recognition

Sl.	Authority	Responsibilities	Communication Details
1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
5	Website/Portal (Helpdesk)	Queries regarding NDLI and its services	support@ndl.gov.in
6	Contents and Copyright Issues	Queries related to content curation and copyright issues	content@ndl.gov.in
7	National Digital Library of India Club (NDLI Club)	Queries related to NDLI Club formation, support, user awareness program, seminar/symposium, collaboration, social media, promotion, and outreach	clubsupport@ndl.gov.in
8	Digital Preservation Centre (DPC)	Assistance with digitizing and archiving copyright-free printed books	dpc@ndl.gov.in
9	IDR Setup or Support	Queries related to establishment and support of Institutional Digital Repository (IDR) and IDR workshops	idr@ndl.gov.in

Effect of gadobutrol on VX2 magnetic resonance diffusion-weighted imaging

Coma Duration Prediction in Diffuse Axonal Injury: Analyses of Apparent Diffusion Coefficient and Clinical Prognostic Factors

Quantitative investigative analysis of tumour separability in the prostate gland using ultra-high b-value computed diffusion imaging

Isotropic anomalous filtering in Diffusion-Weighted Magnetic Resonance Imaging

Multiparametric MRI prostate cancer analysis via a hybrid morphological-textural model

Cross-device automated prostate cancer localization with multiparametric MRI

Prostate cancer localization by novel magnetic resonance dispersion imaging

An Information Theoretic Approach Characterizing Diffusion Anisotropy in Diffusion-weighted Magnetic Resonance Images

Anisotropic anomalous diffusion filtering applied to relaxation time estimation in magnetic resonance imaging

Non-parametric Bayesian estimation of apparent diffusion coefficient from diffusion-weighted magnetic resonance imaging data

Similar Documents

Effect of gadobutrol on VX2 magnetic resonance diffusion-weighted imaging

Coma Duration Prediction in Diffuse Axonal Injury: Analyses of Apparent Diffusion Coefficient and Clinical Prognostic Factors

Quantitative investigative analysis of tumour separability in the prostate gland using ultra-high b-value computed diffusion imaging

Isotropic anomalous filtering in Diffusion-Weighted Magnetic Resonance Imaging

Multiparametric MRI prostate cancer analysis via a hybrid morphological-textural model

Cross-device automated prostate cancer localization with multiparametric MRI

Prostate cancer localization by novel magnetic resonance dispersion imaging

An Information Theoretic Approach Characterizing Diffusion Anisotropy in Diffusion-weighted Magnetic Resonance Images

Anisotropic anomalous diffusion filtering applied to relaxation time estimation in magnetic resonance imaging

Non-parametric Bayesian estimation of apparent diffusion coefficient from diffusion-weighted magnetic resonance imaging data