Analysis of Inter-Rater Reliability of the Mammography Assessment after Image Processing

Analysis of Inter-Rater Reliability of the Mammography

Assessment after Image Processing

IWBBIO 2015Granada / SPAIN

Aslı YAZAĞANR.T.E.U

Rize / TURKEY

15.04.2015 IWBBIO 2015 Aslı Yazağan





IMAGE PROCESSING



This visual difference hides any valuable diagnostic information for

the detection of abnormalities ?


Introduction

Subjective interpretation of mammograhy images. Mammography Decision Support System (MDSS) Important not losing diagnostic information after image

processing for system performance


Classification of Mass

Mass Detection

Image Enhancement( Median Filtering, Wavelet Based Thresholding, CLAHE, Anizot-opik

Diffusion Filtering )

MDSS System Performance

Introduction

Radiologists’ consistency in their interpretation before and after image processing?

How to understand the concept of radiologists’ disagreement and observer variability.

Two measurements for reliability:1. Intra-rater Reliability

One person should come out with the same results on every repetition of the test.2. Inter-rater Reliability

The degree of agreement among raters


Objective of the Study

To test the consistency of radiologists’ evaluation before and after image enhancement

Research Question

Does image enhancement step cause any diagnostic data loss that affects radiologists’ decision?


Methodology

Collection of Mammography ImagesEvaluation of ImagesObserver Consistency


Methodology > Collection of Mammography Images

Database of the Mammographic Image Analysis Society (MIAS) was used.

50 mammogram from MIAS database 20 images include tumors 20 images include calcification 10 normal images


Methodology > Evaluation of Images

2 female – 3 male radiologists screened and marked selected images before and after image enchancement process.

3 months interval between two sessions to reduce the influence of learning effects on the results.



Radiologists decided

Is there a mass or calcification the number of abnormalities the abnormality level of the suspicious region

Evaluation results from all radiologists were combined for each image as two scores as indications of doctors’ decisions before and after image enhancement.

The closeness of the scores indicates the consistency of the radiologists’ decision on that image.


Methodology > Observer Consistency

The consistency of radiologists’ evaluation is assessed by inter-rater reliability statistics.

Cronbach’s Alpha, Sperman Correlation, Pearson's R and Kappa statistics were used to evaluate radiologist reading consistency.


Results


Three radiologists had high consistency especially according to Cronbach's Alpha.

Two radiologists showed a moderate consistency. Inconsistency might depend on other factors such as experience, age, sex, psychological situation etc.

That mass detection performance is more consistent than calcification detection. It is decided to use other image processing methods for calcification images.

Discussions


Diagnostic performance studies depend on radiological problem domain image processing techniques that used in the study.

How to infer a general judgment that image processing improves or reduces radiologists’ diognostic quality.

Wide and long term projects should be planned for generic usage that helps radiologists’ interpretation of images

Image Processed ImageApplying an Image processing technique Improves Radiologists’

diagnostic quality ??

Conclusion


This is a part of MDSS project. Important not losing diagnostic information after image

enhancement for accurate classification of abnormalities for MDSS.

Diagnostic information lost is tested by radiologists. This study focuses on the consistency of radiologists’

evaluation before and after image enhancement.

Similar studies needs to be conducted before designing medical decision support systems.

Thank you &

Questions?

[email protected]



Radiologists decided the number of abnormalities the abnormality level of the suspicious region

Rows represent abnormality counts for each image.

Columns represent the degree of the probability of being malign of those regions


Education

Analysis of Inter-Rater Reliability of the Mammography Assessment after Image Processing