McDaniels – Dec 19, 2008. Outline ADC Calculations – Estimation of placement uncertainty – Effect on Set 1 and Set 2 values.

Slides:

Advertisements

Similar presentations

Inferences based on TWO samples

Advertisements

June 9, 2008Stat Lecture 8 - Sampling Distributions 1 Introduction to Inference Sampling Distributions Statistics Lecture 8.

Statistics 1: Introduction to Probability and Statistics Section 3-3.

Random Variables and Expectation. Random Variables A random variable X is a mapping from a sample space S to a target set T, usually N or R. Example:

Propagation of Error Ch En 475 Unit Operations. Quantifying variables (i.e. answering a question with a number) 1. Directly measure the variable. - referred.

McDaniels – Sept 12, Outline Uncertainty in ADC value Correction Manuscript.

The Dependence of the Apparent Diffusion Coefficient on Voxel Location and Calculation Method Lars Ewell 1, Naren Vijayakumar Meeting of the American.

The University of Akron Dept of Business Technology Computer Information Systems The Relational Model: Query-By-Example (QBE) 2440: 180 Database Concepts.

1 Research Update LAE 9/26/08. 2 Uncertainty in Apparent Diffusion Coefficients Determined from Diffusion Weighted Magnetic Resonance Imaging

1 Research Update/Review LAE 5/23/08. 2 RIN/Recurrent Disease: The Problem T1 weighted contrast enhanced MRI taken 16 months after completion of radiotherapy.

McDaniels – Oct 24, Outline MRI Image uncertainty Point uncertainty ADC uncertainty.

ADC Change with Pixel Shift Joshua Kim June 12, 2009.

1 Research Update LAE 8/22/08. 2 Uncertainty in Transcription of Lesion Contours to Diffusion Weighted Magnetic Resonance Images

McDaniels – Oct 10, Outline Geometric Uncertainty Uncertainty in average intensity due to lesion placement ADC uncertainty.

Part 4 Chapter 13 Linear Regression

McDaniels – Sept 26, Outline Patient 5 Exam 6 ADC uncertainty Manuscript.

Variability Measures of spread of scores range: highest - lowest standard deviation: average difference from mean variance: average squared difference.

ADC Calculations Joshua Kim. I. Objective and Goals II. Current ADC Results III. Current Progress on MatLab Program Outline.

McDaniels – Feb 29, Outline Patient 6 question Patient 11 ADC results Abstract for AAPM conference.

Timed. Transects Statistics indicate that overall species Richness varies only as a function of method and that there is no difference between sites.

Stat 2411 Statistical Methods Chapter 4. Measure of Variation.

McDaniels – April 25, Outline Patient 13 ADC Values Progress Update Patient 7 issues.

ADC Change with Pixel Shift Joshua Kim. I.Review II.Analysis Procedure III.ADC and Error Calculations IV.Current ADC Variation Results V.Future Work Outline.

2.3. Measures of Dispersion (Variation):

McDaniels – Dec 5, Outline ADC Calculations – Estimation of placement uncertainty – Effect on Set 1 and Set 2 values.

McDaniels – Feb 8, Outline Patient 12 ADC results Whole lesion plots – Contour weighting factor.

Method for Determining Apparent Diffusion Coefficient Values for Cerebral Lesions from Diffusion Weighted Magnetic Resonance Imaging Examinations T.H.

Variance and Standard Deviation. Variance: a measure of how data points differ from the mean Data Set 1: 3, 5, 7, 10, 10 Data Set 2: 7, 7, 7, 7, 7 What.

Jump Detection and Analysis Investigation of Media/Telecomm Industry Prad Nadakuduty Presentation 3 3/5/08.

Quantitative Skills: Data Analysis

A How-To Guide on Reading Grade Equivalent Scores By Abby Helterbrand and Kate Evans.

8 Sampling Distribution of the Mean Chapter8 p Sampling Distributions Population mean and standard deviation,  and   unknown Maximal Likelihood.

Propagation of Error Ch En 475 Unit Operations. Quantifying variables (i.e. answering a question with a number) 1. Directly measure the variable. - referred.

Physics 114: Lecture 14 Mean of Means Dale E. Gary NJIT Physics Department.

University of Montreal & iMAGIS A Light Hierarchy for Fast Rendering of Scenes with Many Lights E. Paquette, P. Poulin, and G. Drettakis.

Statistics 1: Introduction to Probability and Statistics Section 3-2.

The chi-squared statistic  2 N Measures “goodness of fit” Used for model fitting and hypothesis testing e.g. fitting a function C(p 1,p 2,...p M ; x)

Introduction to Inference Sampling Distributions.

ES 07 These slides can be found at optimized for Windows)

How Can We Describe the Spread of Quantitative Data? 1.

CHAPTER 2: Basic Summary Statistics

7.5 The Variance and Standard Deviation

Stat 2411 Statistical Methods Chapter 4. Measure of Variation.

Evaluating Hypotheses. Outline Empirically evaluating the accuracy of hypotheses is fundamental to machine learning – How well does this estimate its.

Measures of Variation. Variation Variation describes how widely data values are spread out about the center of a distribution.

Copyright © 2015, 2012, and 2009 Pearson Education, Inc. 1 Chapter Descriptive Statistics 2.

Lecture notes 13: ANOVA (a.k.a. Analysis of Variance)

Welcome to Week 03 Tues MAT135 Statistics

Describing Distributions of Quantitative Data

Copyright 2015 Davitily.

Application of the Bootstrap Estimating a Population Mean

Graphing in Calculator

Stat 2411 Statistical Methods

Aspect 1: Recording RAW data

به نام خدایی که یاد او، مایه ی آرامش واقعی است.

Statistics Variability

Common Core Math I Unit 1 Day 2 Frequency Tables and Histograms

Measurement Uncertainty Analysis

How do we categorize and make sense of data?

Chapter 2 Exploring Data with Graphs and Numerical Summaries

Statistics 1: Introduction to Probability and Statistics

CHAPTER- 3.1 ERROR ANALYSIS.

Stat 2411 Statistical Methods Chapter 4. Measure of Variation.

Unit 3 Review (Calculator)

CHAPTER 2: Basic Summary Statistics

Common Core Math I Unit 1 Day 2 Frequency Tables and Histograms

2.3. Measures of Dispersion (Variation):

Calculate 9 x 81 = x 3 3 x 3 x 3 x 3 3 x 3 x 3 x 3 x 3 x 3 x =

Presentation transcript:

McDaniels – Dec 19, 2008

Outline ADC Calculations – Estimation of placement uncertainty – Effect on Set 1 and Set 2 values

Placement uncertainty b=0, 520, 850 images Placed ROI, recorded average intensity Moved ROI by 2% of image size, recorded intensity Measured intensity at original location +/- 2% voxel in every direction Variance of 2-3% for all b-values of patient 5 Variance of 9-14% for patient 6 (inferior location

Overall effect on set 1 and set 2 numbers Previous uncertainty in ADC value – Set 1 – 7.5% – Set 2 – 21.0% Considering uncertainty due to ROI placement – Set 1 – 8.1% – Set 2 – 25.9%

Caveat Seems to be more dependent on individual image statistics May be better to estimate based on image – Variance within image high – Uncertainty based on average intensity might be OK – Approximation based on max and min intensity (intensity spread)