You have requested a machine translation of selected content from our databases. This functionality is provided solely for your convenience and is in no way intended to replace human translation. Neither SPIE nor the owners and publishers of the content make, and they explicitly disclaim, any express or implied representations or warranties of any kind, including, without limitation, representations and warranties as to the functionality of the translation feature or the accuracy or completeness of the translations.
Translations are not retained in our system. Your use of this feature and the translations is subject to all use restrictions contained in the Terms and Conditions of Use of the SPIE website.
11 March 2014Comparing observer models and feature selection methods for a task-based statistical assessment of digital breast tomsynthesis in reconstruction space
A task-based assessment of image quality1 for digital breast tomosynthesis (DBT) can be done in either the projected or reconstructed data space. As the choice of observer models and feature selection methods can vary depending on the type of task and data statistics, we previously investigated the performance of two channelized- Hotelling observer models in conjunction with 2D Laguerre-Gauss (LG) and two implementations of partial least squares (PLS) channels along with that of the Hotelling observer in binary detection tasks involving DBT projections.2, 3 The difference in these observers lies in how the spatial correlation in DBT angular projections is incorporated in the observer’s strategy to perform the given task. In the current work, we extend our method to the reconstructed data space of DBT. We investigate how various model observers including the aforementioned compare for performing the binary detection of a spherical signal embedded in structured breast phantoms with the use of DBT slices reconstructed via filtered back projection. We explore how well the model observers incorporate the spatial correlation between different numbers of reconstructed DBT slices while varying the number of projections. For this, relatively small and large scan angles (24° and 96°) are used for comparison. Our results indicate that 1) given a particular scan angle, the number of projections needed to achieve the best performance for each observer is similar across all observer/channel combinations, i.e., Np = 25 for scan angle 96° and Np = 13 for scan angle 24°, and 2) given these sufficient numbers of projections, the number of slices for each observer to achieve the best performance differs depending on the channel/observer types, which is more pronounced in the narrow scan angle case.
Subok Park,George Z. Zhang,Rongping Zeng, andKyle J. Myers
"Comparing observer models and feature selection methods for a task-based statistical assessment of digital breast tomsynthesis in reconstruction space", Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370M (11 March 2014); https://doi.org/10.1117/12.2043598
The alert did not successfully save. Please try again later.
Subok Park, George Z. Zhang, Rongping Zeng, Kyle J. Myers, "Comparing observer models and feature selection methods for a task-based statistical assessment of digital breast tomsynthesis in reconstruction space," Proc. SPIE 9037, Medical Imaging 2014: Image Perception, Observer Performance, and Technology Assessment, 90370M (11 March 2014); https://doi.org/10.1117/12.2043598