Automatic shadow detection in 2D ultrasound images
Meng Q, Baumgartner C, Sinclair M, Housden J, Rajchl M, Gomez A, Hou B, Toussaint N, Zimmer V, Tan J, Matthew J, Rueckert D, Schnabel J, Kainz B (2018)
Publication Type: Conference contribution
Publication year: 2018
Journal
Publisher: Springer Verlag
Book Volume: 11076 LNCS
Pages Range: 66-75
Conference Proceedings Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Event location: Granada, ESP
ISBN: 9783030008062
DOI: 10.1007/978-3-030-00807-9_7
Abstract
Automatically detecting acoustic shadows is of great importance for automatic 2D ultrasound analysis ranging from anatomy segmentation to landmark detection. However, variation in shape and similarity in intensity to other structures make shadow detection a very challenging task. In this paper, we propose an automatic shadow detection method to generate a pixel-wise, shadow-focused confidence map from weakly labelled, anatomically-focused images. Our method: (1) initializes potential shadow areas based on a classification task. (2) extends potential shadow areas using a GAN model. (3) adds intensity information to generate the final confidence map using a distance matrix. The proposed method accurately highlights the shadow areas in 2D ultrasound datasets comprising standard view planes as acquired during fetal screening. Moreover, the proposed method outperforms the state-of-the-art quantitatively and improves failure cases for automatic biometric measurement.
Authors with CRIS profile
Involved external institutions
Imperial College London / The Imperial College of Science, Technology and Medicine
United Kingdom (GB)
Eidgenössische Technische Hochschule Zürich (ETHZ) / Swiss Federal Institute of Technology in Zurich
Switzerland (CH)
King’s College London
United Kingdom (GB)
United Kingdom (GB)
Eidgenössische Technische Hochschule Zürich (ETHZ) / Swiss Federal Institute of Technology in Zurich
Switzerland (CH)
King’s College London
United Kingdom (GB)
How to cite
APA:
Meng, Q., Baumgartner, C., Sinclair, M., Housden, J., Rajchl, M., Gomez, A.,... Kainz, B. (2018). Automatic shadow detection in 2D ultrasound images. In Andrew Melbourne, Rosalind Aughwane, Emma Robinson, Roxane Licandro, Melanie Gau, Martin Kampel, Matthew DiFranco, Paolo Rota, Roxane Licandro, Pim Moeskops, Ernst Schwartz, Antonios Makropoulos (Eds.), Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (pp. 66-75). Granada, ESP: Springer Verlag.
MLA:
Meng, Qingjie, et al. "Automatic shadow detection in 2D ultrasound images." Proceedings of the 1st International Workshop on Data Driven Treatment Response Assessment, DATRA 2018 and 3rd International Workshop on Preterm, Perinatal, and Paediatric Image Analysis, PIPPI 2018 Held in Conjunction with 21st International Conference on Medical Image Computing and Computer-Assisted Intervention, MICCAI 2018, Granada, ESP Ed. Andrew Melbourne, Rosalind Aughwane, Emma Robinson, Roxane Licandro, Melanie Gau, Martin Kampel, Matthew DiFranco, Paolo Rota, Roxane Licandro, Pim Moeskops, Ernst Schwartz, Antonios Makropoulos, Springer Verlag, 2018. 66-75.
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