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Automatic shadow detection in 2D ultrasound images

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Title: Automatic shadow detection in 2D ultrasound images
Authors: 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
Item Type: Conference Paper
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.
Issue Date: 15-Sep-2018
Date of Acceptance: 1-Apr-2018
URI: http://hdl.handle.net/10044/1/83316
DOI: 10.1007/978-3-030-00807-9_7
ISBN: 9783030008062
ISSN: 0302-9743
Start Page: 66
End Page: 75
Journal / Book Title: Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume: 11076 LNCS
Copyright Statement: © Springer Nature Switzerland AG 2018. The final publication is available at Springer via https://link.springer.com/chapter/10.1007%2F978-3-030-00807-9_7
Conference Name: International Workshop on Preterm, Perinatal and Paediatric Image Analysis
Keywords: Science & Technology
Technology
Computer Science, Artificial Intelligence
Computer Science, Theory & Methods
Imaging Science & Photographic Technology
Computer Science
SEGMENTATION
Artificial Intelligence & Image Processing
Publication Status: Published
Start Date: 2018-09-16
Conference Place: Granada, Spain
Open Access location: https://openreview.net/pdf?id=SkU16Ec5f
Online Publication Date: 2018-09-15
Appears in Collections:Computing