A computational tool as support in B-mode ultrasound diagnostic quality control

被引:0
作者
Senra Filho, Antonio Carlos Silva da [1 ]
Rodrigues, Erbe Pandini [2 ]
Elias Junior, Jorge [3 ]
Carneiro, Antonio Adilton Oliveira [1 ]
机构
[1] Department of Physics, University of São Paulo – USP, Av. Bandeirantes, Monte Alegre Ribeirão Preto, 3900, SP
[2] Rad Tech Sistemas Médicos, Ribeirão Preto, SP
[3] Department of Medical Clinics, University of São Paulo – USP, Ribeirão Preto, SP
来源
Revista Brasileira de Engenharia Biomedica | 2014年 / 30卷 / 04期
关键词
B-mode; Quality control; Ultrasound;
D O I
10.1590/1517-3151.0644
中图分类号
学科分类号
摘要
Introduction: The quality control (QC) of biomedical equipment is a very important process for the quality assurance of the instruments used in diagnoses and treatments. Ultrasound diagnostic imaging is one of the most widely used techniques for diagnostic imaging in hospitals and medical clinics. However, the time required to complete several B-mode imaging QC tests in ultrasound equipment is very critical for a hospital with a high number of exams. Here, we present a computational tool to assist in the acquisition and storage of data from multiple QC tests in B-mode ultrasound diagnostic equipment to promote an efficient alternative for QC in clinical routines. Methods: The project was planned and implemented in C++ programming language and compiled for two computing platforms: Windows and Linux. The most common QC routine tests for B-mode ultrasound were combined in a simple graphical user interface. Results: After entering all of the correct QC information in the graphical user interface, a final report in PDF format was created. Conclusion: The proposed program has been helpful for students and diagnostic professionals and is a quick and easy application for several QC tests for B-mode ultrasound diagnostic equipment. Our program seeks to help in the dissemination and application of QC tests for B-mode ultrasound equipment in hospitals and clinics and for the technical training of ultrasound professionals. © 2014 Sociedade Brasileira de Engenharia Biomedica. All rights reserved.
引用
收藏
页码:402 / 405
页数:3
相关论文
共 50 条
[31]   Improving B-mode ultrasound diagnostic performance for focal liver lesions using deep learning: A multicentre study [J].
Yang, Qi ;
Wei, Jingwei ;
Hao, Xiaohan ;
Kong, Dexing ;
Yu, Xiaoling ;
Jiang, Tianan ;
Xi, Junqing ;
Cai, Wenjia ;
Luo, Yanchun ;
Jing, Xiang ;
Yang, Yilin ;
Cheng, Zhigang ;
Wu, Jinyu ;
Zhang, Huiping ;
Liao, Jintang ;
Zhou, Pei ;
Song, Yu ;
Zhang, Yao ;
Han, Zhiyu ;
Cheng, Wen ;
Tang, Lina ;
Liu, Fangyi ;
Dou, Jianping ;
Zheng, Rongqin ;
Yu, Jie ;
Tian, Jie ;
Liang, Ping .
EBIOMEDICINE, 2020, 56
[32]   Addressing spatiotemporal distortion of high-speed tissue motion in B-mode ultrasound [J].
Mallory, Ann ;
Donnelly, Bruce ;
Liu, Jun ;
Bahner, David ;
Moorhouse, Kevin ;
Dupaix, Rebecca .
BIOMEDICAL PHYSICS & ENGINEERING EXPRESS, 2018, 4 (05)
[33]   AUTOMATIC OPTIC NERVE MEASUREMENT: A NEW TOOL TO STANDARDIZE OPTIC NERVE ASSESSMENT IN ULTRASOUND B-MODE IMAGES [J].
Meiburger, Kristen M. ;
Naldi, Andrea ;
Michielli, Nicola ;
Coppo, Lorenzo ;
Fassbender, Klaus ;
Molinari, Filippo ;
Lochner, Piergiorgio .
ULTRASOUND IN MEDICINE AND BIOLOGY, 2020, 46 (06) :1533-1544
[34]   Comparative Effectiveness of Elastographic and B-Mode Ultrasound Criteria for Diagnostic Discrimination of Thyroid Nodules: A Meta-Analysis [J].
Razavi, Seyed Amirhossein ;
Hadduck, Tyson A. ;
Sadigh, Gelareh ;
Dwamena, Ben A. .
AMERICAN JOURNAL OF ROENTGENOLOGY, 2013, 200 (06) :1317-1326
[35]   Image quality and detection of pathology by ultrasound: Comparison of B-mode ultrasound with photopic imaging and tissue harmonic imaging alone and in combination [J].
Fischer, T ;
Filimonow, S ;
Taupitz, M ;
Petersein, J ;
Beyersdorff, D ;
Bollow, M ;
Hamm, B .
ROFO-FORTSCHRITTE AUF DEM GEBIET DER RONTGENSTRAHLEN UND DER BILDGEBENDEN VERFAHREN, 2002, 174 (10) :1313-1317
[36]   NONLINEAR PROCESSING IN B-MODE ULTRASOUND AFFECTS CAROTID DIAMETER ASSESSMENT [J].
Rossi, Alessandro C. ;
Brands, Peter J. ;
Hoeks, Arnold P. G. .
ULTRASOUND IN MEDICINE AND BIOLOGY, 2009, 35 (05) :736-747
[37]   Automated localization and segmentation techniques for B-mode ultrasound images: A review [J].
Meiburger, Kristen M. ;
Acharya, U. Rajendra ;
Molinari, Filippo .
COMPUTERS IN BIOLOGY AND MEDICINE, 2018, 92 :210-235
[38]   Advancements in Deep Learning for B-Mode Ultrasound Segmentation: A Comprehensive Review [J].
Ansari, Mohammed Yusuf ;
Mangalote, Iffa Afsa Changaai ;
Meher, Pramod Kumar ;
Aboumarzouk, Omar ;
Al-Ansari, Abdulla ;
Halabi, Osama ;
Dakua, Sarada Prasad .
IEEE TRANSACTIONS ON EMERGING TOPICS IN COMPUTATIONAL INTELLIGENCE, 2024, 8 (03) :2126-2149
[39]   PDMS Composites with Photostable NIR Dyes for B-Mode Ultrasound Imaging [J].
Thompson, India Lewis ;
Mathews, Sunish ;
Zhang, Edward ;
Beard, Paul ;
Desjardins, Adrien ;
Colchester, Richard .
2022 IEEE INTERNATIONAL ULTRASONICS SYMPOSIUM (IEEE IUS), 2022,
[40]   Breast-lesion Segmentation Combining B-Mode and Elastography Ultrasound [J].
Pons, Gerard ;
Marti, Joan ;
Marti, Robert ;
Ganau, Sergi ;
Noble, J. Alison .
ULTRASONIC IMAGING, 2016, 38 (03) :209-224