Optimization and Application Analysis of Phase Correction Method Based on Improved Image Registration in Ultrasonic Image Detection

被引:1
作者
Lu, Nannan [1 ]
Shu, Hongyan [1 ]
机构
[1] Huangshi Matern & Childrens Hlth Hosp, Dept Ultrasound Med, Huangshi, Hubei, Peoples R China
关键词
application optimization; health care; image detection; image registration; phase correction; ultrasound images; VESSEL-BASED REGISTRATION; INTRAOPERATIVE ULTRASOUND; 2D ULTRASOUND; 3D; COMPRESSION; TOMOGRAPHY; VALIDATION; GUIDANCE;
D O I
10.1002/ima.23185
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
In order to prevent and detect a wide range of disorders, including those of the brain, thoracic, digestive, urogenital, and cardiovascular systems, ultrasound technology is essential for assessing physiological data and tissue morphology. Its capacity to deliver real-time, high-frequency scans makes it a handy and non-invasive diagnostic tool. However, issues like patient movements and probe jitter from human error can provide a large amount of interference, resulting in inaccurate test findings. Techniques for image registration can assist in locating and eliminating unwanted interference while maintaining crucial data. Even though there has been research on improving these techniques in Matlab, there are no specialized systems for interference removal, and the procedure is still time-consuming, particularly when working with huge quantities of ultrasound images. The phase correlation technique, which converts images into the frequency domain and makes noise suppression easier, is one of the most efficient algorithms now in use since it can tolerate noise with resilience. Nevertheless, little research has been done on using this technique to identify displacement in blood vessel wall ultrasound images. To address these gaps, this work presents an image registration system that uses the phase correlation algorithm. The system provides rotation, zoom registration, picture translation, and displacement detection of the vessel wall in addition to interference removal. Furthermore, batch processing is included to increase the effectiveness of registering multiple ultrasound pictures. Through efficient interference management and streamlined registration, this method offers a workable way to improve the precision and efficacy of ultrasonic diagnostics.
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页数:12
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共 44 条
[1]   Automatic skin lesions detection from images through microscopic hybrid features set and machine learning classifiers [J].
Alyami, Jaber ;
Rehman, Amjad ;
Sadad, Tariq ;
Alruwaythi, Maryam ;
Saba, Tanzila ;
Bahaj, Saeed Ali .
MICROSCOPY RESEARCH AND TECHNIQUE, 2022, 85 (11) :3600-3607
[2]   Registration of dynamic multiview 2D ultrasound and late gadolinium enhanced images of the heart: Application to hypertrophic cardiomyopathy characterization [J].
Betancur, Julian ;
Simon, Antoine ;
Halbert, Edgar ;
Tavard, Francois ;
Carre, Francois ;
Hernandez, Alfredo ;
Donal, Erwan ;
Schnell, Frederic ;
Garreau, Mireille .
MEDICAL IMAGE ANALYSIS, 2016, 28 :13-21
[3]   Cross contrast multi-channel image registration using image synthesis for MR brain images [J].
Chen, Min ;
Carass, Aaron ;
Jog, Amod ;
Lee, Junghoon ;
Roy, Snehashis ;
Prince, Jerry L. .
MEDICAL IMAGE ANALYSIS, 2017, 36 :2-14
[4]   Validation of a hybrid Doppler ultrasound vessel-based registration algorithm for neurosurgery [J].
Chen, Sean Jy-Shyang ;
Reinertsen, Ingerid ;
Coupe, Pierrick ;
Yan, Charles X. B. ;
Mercier, Laurence ;
Del Maestro, D. Rolando ;
Collins, D. Louis .
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2012, 7 (05) :667-685
[5]   Intraoperative ultrasound for guidance and tissue shift correction in image-guided neurosurgery [J].
Comeau, RM ;
Sadikot, AF ;
Fenster, A ;
Peters, TM .
MEDICAL PHYSICS, 2000, 27 (04) :787-800
[6]   Realization of a biomechanical model-assisted image guidance system for breast cancer surgery using supine MRI [J].
Conley, Rebekah H. ;
Meszoely, Ingrid M. ;
Weis, Jared A. ;
Pheiffer, Thomas S. ;
Arlinghaus, Lori R. ;
Yankeelov, Thomas E. ;
Miga, Michael I. .
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2015, 10 (12) :1985-1996
[7]   IBIS: an OR ready open-source platform for image-guided neurosurgery [J].
Drouin, Simon ;
Kochanowska, Anna ;
Kersten-Oertel, Marta ;
Gerard, Ian J. ;
Zelmann, Rina ;
De Nigris, Dante ;
Beriault, Silvain ;
Arbel, Tal ;
Sirhan, Denis ;
Sadikot, Abbas F. ;
Hall, Jeffery A. ;
Sinclair, David S. ;
Petrecca, Kevin ;
DelMaestro, Rolando F. ;
Collins, D. Louis .
INTERNATIONAL JOURNAL OF COMPUTER ASSISTED RADIOLOGY AND SURGERY, 2017, 12 (03) :363-378
[8]   Speckle Noise Reduction in Ultrasound Images for Improving the Metrological Evaluation of Biomedical Applications: An Overview [J].
Duarte-Salazar, Carlos A. ;
Eduardo Castro-Ospina, Andres ;
Becerra, Miguel A. ;
Delgado-Trejos, Edilson .
IEEE ACCESS, 2020, 8 :15983-15999
[9]   Registration of renal SPECT and 2.5D US images [J].
Galdames, Francisco J. ;
Perez, Claudio A. ;
Estevez, Pablo A. ;
Held, Claudio M. ;
Jaillet, Fabrice ;
Lobo, Gabriel ;
Donoso, Gilda ;
Coll, Claudia .
COMPUTERIZED MEDICAL IMAGING AND GRAPHICS, 2011, 35 (04) :302-314
[10]   Progress in the Application of Portable Ultrasound Combined with Artificial Intelligence in Pre-Hospital Emergency and Disaster Sites [J].
Gao, Xing ;
Lv, Qi ;
Hou, Shike .
DIAGNOSTICS, 2023, 13 (21)