Alignment of Viewing-Angle Dependent Ultrasound Images

作者: Christian Wachinger , Nassir Navab

DOI: 10.1007/978-3-642-04268-3_96

关键词: WeightingMatching (graph theory)SignalUltrasoundTransducerUltrasound imagingPhase (waves)Feature (computer vision)Artificial intelligenceScatteringViewing angleComputer visionComputer science

摘要: We address the problem of viewing-angle dependency ultrasound images for registration. The reflected signal from large scale tissue boundaries is dependent on incident angle beam. This applies an implicit weighting image, viewing-angle, which negatively affects registration process, especially when utilizing curved linear transducers. show that a simple reweighting images, considering common physical model imaging, not feasible. therefore introduce new matching function, separating reflectivity and scattering regions, are results two different types interactions beam with tissue. use local phase identifying regions reflectivity, consider it as one part our combining feature- intensity-based aspects. First experiments provide good this novel approach.

参考文章(18)
Wolfgang Henrich, Annette Schmider, Siri Kjos, Boris Tutschek, Joachim W. Dudenhausen, Advantages of and applications for extended field-of-view ultrasound in obstetrics. Archives of Gynecology and Obstetrics. ,vol. 268, pp. 121- 127 ,(2003) , 10.1007/S00404-002-0367-7
Djamal Boukerroui, J. Alison Noble, Michael Brady, Velocity estimation in ultrasound images: a block matching approach. international conference information processing. ,vol. 18, pp. 586- 598 ,(2003) , 10.1007/978-3-540-45087-0_49
Dong Ni, Yingge Qu, Xuan Yang, Yim Pan Chui, Tien-Tsin Wong, Simon S. M. Ho, Pheng Ann Heng, Volumetric Ultrasound Panorama Based on 3D SIFT medical image computing and computer assisted intervention. ,vol. 11, pp. 52- 60 ,(2008) , 10.1007/978-3-540-85990-1_7
Ilker Hacihaliloglu, Rafeef Abugharbieh, Antony Hodgson, Robert Rohling, Bone Segmentation and Fracture Detection in Ultrasound Using 3D Local Phase Features Medical Image Computing and Computer-Assisted Intervention – MICCAI 2008. ,vol. 11, pp. 287- 295 ,(2008) , 10.1007/978-3-540-85988-8_35
Dale E. Starchman, David L. Hykes, Wayne R. Hedrick, Ultrasound Physics and Instrumentation ,(1985)
Christian Wachinger, Wolfgang Wein, Nassir Navab, Three-dimensional ultrasound mosaicing medical image computing and computer assisted intervention. ,vol. 10, pp. 327- 335 ,(2007) , 10.1007/978-3-540-75759-7_40
Matthew Mellor, Michael Brady, Phase mutual information as a similarity measure for registration Medical Image Analysis. ,vol. 9, pp. 330- 343 ,(2005) , 10.1016/J.MEDIA.2005.01.002
Boaz Cohen, Its’hak Dinstein, New maximum likelihood motion estimation schemes for noisy ultrasound images Pattern Recognition. ,vol. 35, pp. 455- 463 ,(2002) , 10.1016/S0031-3203(01)00053-X
Graeme P. Penney, Lewis D. Griffin, Andrew P. King, David J. Hawkes, A novel framework for multi-modal intensity-based similarity measures based on internal similarity In: Reinhardt, JM and Pluim, JPW, (eds.) (Proceedings) Medical Imaging 2008 Conference. SPIE-INT SOC OPTICAL ENGINEERING (2008). ,vol. 6914, ,(2008) , 10.1117/12.769402