A Hybrid Approach for Virtual Clinical Trials for Mammographic Imaging
Schebesch F, Magdalena H, Mertelmeier T, Maier A, Ritschl L (2018)
Publication Type: Conference contribution
Publication year: 2018
Publisher: SPIE
Edited Volumes: Progress in Biomedical Optics and Imaging - Proceedings of SPIE
Book Volume: 10718
Pages Range: 107180Z
Conference Proceedings Title: Proc. of SPIE
Event location: Atlanta, GA, USA
ISBN: 9781510620070
DOI: 10.1117/12.2318452
Abstract
Detection of lesions is an essential part of making a diagnosis in mammography and therefore is a main focus in the development of algorithms built for image quality assessment. We propose a hybrid approach with an accurate lesion projection model and embedding of lesions into clinical images that already contain relevant structures of anatomical noise. Using an algebraic lesion model, lesions with different sizes and contrasts are generated. The projection algorithm incorporates the modeling of blur effects due to system movement and the physical extent of the anode. Signal and background patches are extracted and used to evaluate channelized Hotelling observers with Laguerre-Gauss channels and with Gabor channels. A four-alternative forced-choice study with five medical imaging experts is performed and the inter-reader agreement with and without the model observers is determined by using Fleiss' kappa. Analyzing three different sizes for tiny, dense lesions and four density levels for larger mass-like lesions we find a good detection rate of the tiny lesions for both human as well as model observers. The inter-reader agreement using the common interpretation of Fleiss' kappa is substantial or better. Comparing full-field digital mammography and digital breast tomosynthesis w.r.t. the different mass densities we find that human readers and model observers perform well on the DBT data and the detection rate drops with lesion contrast as expected. The inter-reader agreement here is fair for the lowest contrast and substantial for the denser cases. Both human readers and model observers show difficulty in detecting the low contrast lesions in FFDM images. The inter-reader agreement is rather poor among all readers. Overall, the results indicate a good agreement between human observers and model observers and a distinctive benefit of 3-D reconstruction over FFDMs for low contrast lesions.
Authors with CRIS profile
Frank Schebesch
Lehrstuhl für Informatik 14 (Bild- und Sprachverarbeitung)
Andreas Maier
Lehrstuhl für Informatik 5 (Mustererkennung)
Involved external institutions
Germany (DE)How to cite
APA:
Schebesch, F., Magdalena, H., Mertelmeier, T., Maier, A., & Ritschl, L. (2018). A Hybrid Approach for Virtual Clinical Trials for Mammographic Imaging. In Proc. of SPIE (pp. 107180Z). Atlanta, GA, USA: SPIE.
MLA:
Schebesch, Frank, et al. "A Hybrid Approach for Virtual Clinical Trials for Mammographic Imaging." Proceedings of the 14th International Workshop on Breast Imaging (IWBI 2018), Atlanta, GA, USA SPIE, 2018. 107180Z.
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