Ms. Laura M. Yarusso Profile

Laura M. Yarusso

at Univ of Chicago

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Author

Publications (5)

Proceedings Article | 9 March 2011 Paper

A comparison study of textural features between FFDM and film mammogram images

Hao Jing, Yongyi Yang, Miles Wernick, Laura Yarusso, Robert Nishikawa

Proc. SPIE. 7963, Medical Imaging 2011: Computer-Aided Diagnosis

KEYWORDS: Breast, Computer aided diagnosis and therapy, Breast cancer, Tissues, Matrices, Diagnostics, Mammography, Computer aided design, Algorithm development, Digital mammography

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Proceedings Article | 3 March 2011 Paper

Analysis of the number of distinct findings obtained by multiple readers in an MRMC study: When do findings obtained from the addition of new readers become redundant, or otherwise negligible?

Sophie Paquerault, Berkman Sahiner, Anna Kettermann, Laura Yarusso, Lubomir Hadjiiski, Heang-Ping Chan

Proc. SPIE. 7966, Medical Imaging 2011: Image Perception, Observer Performance, and Technology Assessment

KEYWORDS: Mathematical modeling, Computer aided diagnosis and therapy, Data modeling, Computing systems, Computer simulations, Lung, Computed tomography, Computer aided design, CAD systems, Solid modeling

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The ultimate goal of this project is to investigate whether the effect of a computer-aided detection (CAD) system on readers' performance (especially, in situation of an upgrade of the CAD system, or between two different CAD systems with similar design) can be accurately predicted without having to perform a multi-reader multi-case (MRMC) observer study and, if such prediction is possible, to establish the underlying methodology. Our current study is intended to provide evidence that would substantiate efforts toward such investigation. The objectives of this study were 1) to investigate the relationship between the number of radiologists reading a dataset of thoracic computed tomography (CT) images to identify lung nodules and the number of distinct findings and 2) to determine the number of readers needed to identify almost all clinically distinct findings in a dataset. We used data from a multi-reader multi-case (MRMC) observer study that consisted of six radiologists interpreting 85 thoracic CT examinations. To further illustrate our approach, we also utilized simulated data consisting of twelve readers interpreting 198 samples equally distributed between three levels of detection difficulty. For each possible reader grouping, the number of distinct findings identified by the readers in the group was calculated. Five types of regression models used to describe the relationship between the average number of distinct findings per case and the number of readers needed were compared. The result showed that the logistic model best fitted both the thoracic CT data and the simulated data. Our assumption is that adding more readers after a certain reader set size would mostly add redundant findings and, therefore, the benefit would be negligible. Using this model, the predicted number of readers was found to depend on the type of findings considered. Our study showed that the number of clinically distinct findings that can be identified by radiologists on CT lung examinations without the use of a CAD system may be limited and that identifying almost all of these findings may only require a limited number of readers.

Proceedings Article | 17 March 2008 Paper

Influence of signal-to-noise ratio and temporal stability on computer-aided detection of mammographic microcalcifications in digitized screen-film and full-field digital mammography

Laura Yarusso, Robert Nishikawa

Proc. SPIE. 6915, Medical Imaging 2008: Computer-Aided Diagnosis

KEYWORDS: Signal to noise ratio, Computer aided diagnosis and therapy, Imaging systems, Sensors, Image segmentation, Bone, Image quality, Mammography, Signal detection, Digital mammography

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Proceedings Article | 12 May 2004 Paper

Potential improvement of computerized classification for malignant versus benign mammographic microcalcification clusters with the use of special views

Sophie Paquerault, Laura Yarusso, John Papaioannou

Proc. SPIE. 5370, Medical Imaging 2004: Image Processing

KEYWORDS: Breast, Computer aided diagnosis and therapy, Databases, Image segmentation, Diagnostics, Feature extraction, Biopsy, Mammography, Feature selection, Computer aided design

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Proceedings Article | 24 June 1998 Paper

Variations in measured performance of CAD schemes due to database composition and scoring protocol

Robert Nishikawa, Laura Yarusso

Proc. SPIE. 3338, Medical Imaging 1998: Image Processing

KEYWORDS: Breast, Computer aided diagnosis and therapy, Databases, Image analysis, Biopsy, Mammography, Analytical research, Computer aided design, Radiology, Digital mammography

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