Neural Network-based Fast Liver Ultrasound Image Segmentation

被引：16

作者：

Ansari, Mohammed Yusuf ^{[1
]}

Mangalote, Iffa Afsa Changaai ^{[1
]}

Masri, Dima ^{[2
]}

Dakua, Sarada Prasad ^{[1
]}

机构：

[1] Hamad Med Corp, Hamad Gen Hosp, Surg, Doha, Qatar

[2] King Faisal Univ, Biomed Engineeting, Al Hufuf, Al Ahsa, Saudi Arabia

来源：

2023 INTERNATIONAL JOINT CONFERENCE ON NEURAL NETWORKS, IJCNN | 2023年

关键词：

Liver; Ultrasound; Segmentation; Fast; FUSION;

D O I：

10.1109/IJCNN54540.2023.10191085

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Ultrasound is quite popular among the clinicians' fraternity, because the machine is cheap, easy to use, and mobile. However, the image is not that easy to study properly, if the examiner does not have adequate expertise. Image segmentation, being the first step to ease the study, is considered crucial. In this paper, we have presented a neural network-based image segmentation that is based on Pyramid Scene Parsing. Additionally, we have studied the importance of removing noise before the actual segmentation. We have tested the method on the data obtained from Hamad Medical Corporation and found Dice coefficient of 0.913 +/- 0.024 while delivering a real-time performance of 37 frames per second.

引用

页数：8

共 50 条

[1] Fast neural network based image segmentation
Skoneczny, S
Szostakowski, J
Iwanowski, M
Orlowski, A
STATISTICAL AND STOCHASTIC METHODS IN IMAGE PROCESSING II, 1997, 3167 : 164 - 171
[2] Rule and Neural Network-Based Image Segmentation of Mice Vertebrae Images
Madireddy, Indeever
Wu, Tongge
CUREUS JOURNAL OF MEDICAL SCIENCE, 2022, 14 (07)
[3] Fast Sequential Feature Extraction for Recurrent Neural Network-Based Hyperspectral Image Classification
Ma, Andong
Filippi, Anthony M.
Wang, Zhangyang
Yin, Zhengcong
Huo, Da
Li, Xiao
Guneralp, Burak
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2021, 59 (07): : 5920 - 5937
[4] Obtaining completely stable cellular neural network templates for ultrasound image segmentation
Lenic, M.
Zazula, D.
Cigale, B.
11TH MEDITERRANEAN CONFERENCE ON MEDICAL AND BIOLOGICAL ENGINEERING AND COMPUTING 2007, VOLS 1 AND 2, 2007, 16 (1-2): : 1013 - 1016
[5] Residual neural network-based fully convolutional network for microstructure segmentation
Jang, Junmyoung
Van, Donghyun
Jang, Hyojin
Baik, Dae Hyun
Yoo, Sang Duk
Park, Jaewoong
Mhin, Sungwook
Mazumder, Jyoti
Lee, Seung Hwan
SCIENCE AND TECHNOLOGY OF WELDING AND JOINING, 2020, 25 (04) : 282 - 289
[6] Neural network-based segmentation of dynamic MR mammographic images
Lucht, R
Delorme, S
Brix, G
MAGNETIC RESONANCE IMAGING, 2002, 20 (02) : 147 - 154
[7] Fast image segmentation using C-means based Fuzzy Hopfield neural network
Kazemi, Farhad Mohamad
Akbarzadeh-T, Mohamad-R.
Rahati, Saeid
Rajabi, Habib
2008 CANADIAN CONFERENCE ON ELECTRICAL AND COMPUTER ENGINEERING, VOLS 1-4, 2008, : 1773 - +
[8] Multichannel Pulse-Coupled Neural Network-Based Hyperspectral Image Visualization
Duan, Puhong
Kang, Xudong
Li, Shutao
Ghamisi, Pedram
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2020, 58 (04): : 2444 - 2456
[9] SEGMENTATION OF RANGE IMAGE BASED ON KOHONEN NEURAL NETWORK
Zou Ning Liu Jian Zhou Manli Li Qing(State Education Commission Res. Lab. for Image Processing & Intelligent Control. Electronic & Information Engineering Dept.
Journal of Electronics(China), 2001, (03) : 237 - 241
[10] Neural network for image segmentation
Skourikhine, AN
Prasad, L
Schlei, BR
APPLICATIONS AND SCIENCE OF NEURAL NETWORKS, FUZZY SYSTEMS, AND EVOLUTIONARY COMPUTATION III, 2000, 4120 : 28 - 35

← 1 2 3 4 5 →