Paper Info
Title
Cascade Marker Removal Algorithm For Thyroid Ultrasound Images
Abstract
During thyroid ultrasound diagnosis, radiologists add markers such as pluses or crosses near a nodule's edge to indicate the location of a nodule. For computer-aided detection, deep learning models achieve classification, segmentation, and detection by learning the thyroid's texture in ultrasound images. Experiments show that manual markers are strong prior knowledge for data-driven deep learning models, which interferes with the judgment mechanism of computer-aided detection systems. Aiming at this problem, this paper proposes cascade marker removal algorithm for thyroid ultrasound images to eliminate the interference of manual markers. The algorithm consists of three parts. First, in order to highlight marked features, the algorithm extracts salient features in thyroid ultrasound images through feature extraction module. Secondly, mask correction module eliminates the interference of other features besides markers' features. Finally, the marker removal module removes markers without destroying the semantic information in thyroid ultrasound images. Experiments show that our algorithm enables classification, segmentation, and object detection models to focus on the learning of pathological tissue features. At the same time, compared with mainstream image inpainting algorithms, our algorithm shows better performance on thyroid ultrasound images. In summary, our algorithm is of great significance for improving the stability and performance of computer-aided detection systems.
Year
DOI
Venue
2020
10.1007/s11517-020-02216-7
MEDICAL & BIOLOGICAL ENGINEERING & COMPUTING
Keywords
DocType
Volume
Diagnosis, Computer-assisted, Diagnostic imaging, Thyroid neoplasms, Deep learning, Ultrasonography
Journal
58
Issue
ISSN
Citations 
11
0140-0118
0
PageRank 
References 
Authors
0.34
0
11
Name
Order
Citations
PageRank
Ying Xiang1145.66
Yulin Zhang201.01
Mei Yu364.45
Xi Wei401.01
Jialin Zhu503.04
Jie Gao62174155.61
Zhiqiang Liu711624.93
Hongqian Shen801.01
Ruixuan Zhang932.45
Xuewei Li1000.34
Ruiguo Yu11912.96