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View all- Kiss GStorve SHaugen BTorp H(2014)Augmented reality based tools for echocardiographic acquisitions2014 IEEE International Ultrasonics Symposium10.1109/ULTSYM.2014.0171(695-698)Online publication date: Sep-2014
HeartPad: real-time visual guidance for cardiac ultrasound
Pages 169 - 176
Abstract
Medical ultrasound is a challenging modality when it comes to image interpretation. The goal we address in this work is to assist the ultrasound examiner and partially alleviate the burden of interpretation. We propose to address this goal with visualization that provides clear cues on the orientation and the correspondence between anatomy and the data being imaged. Our system analyzes the stream of 3D ultrasound data and in real-time identifies distinct features that are basis for a dynamically deformed mesh model of the heart. The heart mesh is composited with the original ultrasound data to create the data-to-anatomy correspondence. The visualization is broadcasted over the internet allowing, among other opportunities, a direct visualization on the patient on a tablet computer. The examiner interacts with the transducer and with the visualization parameters on the tablet. Our system has been characterized by domain specialist as useful in medical training and for navigating occasional ultrasound users.
Supplementary Material
References
[1]
Berlage T., Fox T., Grunst G., Quast K.-J.: Supporting ultrasound diagnosis using an animated 3d model of the heart. In Proceedings of IEEE Multimedia Computing and Systems 1996 (1996), pp. 34--39.
[2]
Bajura M., Fuchs H., Ohbuchi R.: Merging virtual objects with the real world: Seeing ultrasound imagery within the patient. ACM SIGGRAPH Computer Graphics 26, 2 (1992), 203--210.
[3]
Bruckner S., Gröller M.: VolumeShop: An interactive system for direct volume illustration. In Proceedings of IEEE Visualization 2005 (2005), C. T. Silva E. Gröller H. R., (Ed.), pp. 671--678.
[4]
Burns M., Haidacher M., Wein W., Viola I., Gröller M. E.: Feature emphasis and contextual cutaways for multimodal medical visualization. In Proceedings of EuroVis '07 (2007), pp. 275--282.
[5]
Bluteau J., Kitahara I., Kameda Y., Noma H., Kogure K., Ohta Y.: Visual support for medical communication by using projector-based augmented reality and thermal markers. In Proceedings of the International Conference on Augmented Tele-Existence 2005 (2005), pp. 98--105.
[6]
Bruckner S., Rautek P., Viola I., Roberts M., Sousa M., Gröller M.: Hybrid visibility compositing and masking for illustrative rendering. Computers & Graphics, 34 (2010), 361--369.
[7]
Birkeland Å., Solteszova V., Hönigmann D., Gilja O. H., Brekke S., Ropinski T., Viola I.: The ultrasound visualization pipeline - a survey. ArXiv e-prints (2012). arXiv:1206.3975.
[8]
Brattain L., Vasilyev N., Howe R.: Enabling 3d ultrasound procedure guidance through enhanced visualization. In Proceedings of the International Conference on Information Processing in Computer-Assisted Interventions 2012 (2012), pp. 115--124.
[9]
Cohen J., Olano M., Manocha D.: Appearance-preserving simplification. In Proceedings of ACM SIGGRAPH 1998 (1998), pp. 115--122.
[10]
Dickstein K., Cohen-Solal A., Filippatos G., McMurray J. J. V., Ponikowski P., Poole-Wilson P. A., Strmberg A., van Veldhuisen D. J., Atar D., Hoes A. W., Keren A., Mebazaa A., Nieminen M., Priori S. G., Swedberg K., E. S. C. C. f. P. G. C. P. G.: Esc guidelines for the diagnosis and treatment of acute and chronic heart failure 2008. Eur Heart J 29, 19 (Oct 2008), 2388--2442.
[11]
Fattal R., Lischinski D.: Variational classification for visualization of 3d ultrasound data. In Proceedings of IEEE Visualization 2001 (2001), pp. 403--410.
[12]
Harders M., Bianchi G., Knoerlein B.: Multimodal augmented reality in medicine. In Proceedings of the International Conference on Universal Access in Human-Computer Interaction 2007 (2007), pp. 652--658.
[13]
Hung J., Lang R., Flachskampf F., Shernan S., McCulloch M., Adams D., Thomas J., Vannan M., Ryan T.: 3d echocardiography: a review of the current status and future directions. Journal of the American Society of Echocardiography 20, 3 (2007), 213--233.
[14]
Hönigmann D., Ruisz J., Haider C.: Adaptive design of a global opacity transfer function for direct volume rendering of ultrasound data. In Proceedings of IEEE Visualization '03 (2003), pp. 489--496.
[15]
Kalkofen D., Mendez E., Schmalstieg D.: Comprehensible visualization for augmented reality. IEEE Transactions on Visualization and Computer Graphics 15, 2 (2009), 193--204.
[16]
Kalkofen D., Reitinger B., Risholm P., Bornik A.: Integrated medical workflow for augmented reality applications. Workshop on Augmented (2006).
[17]
Le Bellego G., Bucki M., Bricault I.: Using a smart phone for information rendering in computer-aided surgery. In Proceedings of the International Conference on Human-Computer Interaction 2011 (2011), pp. 202--209.
[18]
Linte C., Moore J., Wiles A., Wedlake C., Peters T.: Virtual reality-enhanced ultrasound guidance: a novel technique for intracardiac interventions. Computer Aded Surgery 13, 2 (2008), 82--94.
[19]
Nelson T., Elvins T.: Visualization of 3d ultrasound data. IEEE Computer Graphics and Applications 13, 6 (1993), 50--57.
[20]
Orderud F., Torp H., Rabben S.: Automatic alignment of standard views in 3d echocardiograms using real-time tracking. In Procedings of the SPIE 7265 (2009), p. 72650D.
[21]
Øye O. K., Ulvang D. M., Gilja O. H., Hauser H., Viola I.: Illustrative couinaud segmentation for ultrasound liver examinations. In Smart Graphics, vol. 6815 of Lecture Notes in Computer Science. Springer Berlin / Heidelberg, 2011, pp. 60--77.
[22]
Petersch B., Hönigmann D.: Blood flow in its context: Combining 3D B-mode and color Doppler us data. IEEE TVCG 13, 4 (2007), 748--757.
[23]
Pieper S., Weidenbach M., Berlage T.: Registration of 3d ultrasound images to surface models of the heart. Proceedings of the Interface to Real & Virtual Worlds (1997), 211--213.
[24]
Snare S., Aase S., Mjlstad O., Dalen H., Orderud F., Torp H.: Automatic real-time view detection. In Ultrasonics Symposium (IUS), 2009 IEEE International (sept. 2009), pp. 2304--2307.
[25]
Stetten G., Chib V.: Overlaying ultrasonographic images on direct vision. Journal of Utrasound in Medicine 20, 3 (2001), 235--240.
[26]
Stetten G., Chib V., Tamburo R.: Tomographic reflection to merge ultrasound images with direct vision. In Proceedings of the IEEE Workshop on Applied Imagery Pattern Recognition (2000), pp. 200--205.
[27]
Stüdeli T., Kalkofen D., Risholm P., Ali W., Freudenthal A., Samset E.: Visualization tool for improved accuracy in needle placement during percutaneous radio-frequency ablation of liver tumors. Proceedings of the SPIE 6918 (2008), 69180B.
[28]
State A., Livingston M., Garrett W., G. H., Whitton M., Pisano E., Fuchs H.: Technologies for augmented reality systems: Realizing ultrasound-guided needle biopsies. In Proceedings of ACM SIGGRAPH 1998 (1998), pp. 439--446.
[29]
Sakas G., Schreyer L.-A., Grimm M.: Preprocessing and volume rendering of 3D ultrasonic data. IEEE Computer Graphics and Applications 15, 4 (1995), 47--54.
[30]
Tang S. L., Kwoh C. K., Teo M. Y., Sing N. W., Ling K. V.: Augmented reality systems for medical applications. IEEE engineering in medicine and biology magazine: the quarterly magazine of the Engineering in Medicine & Biology Society 17, 3 (1998), 49--58.
[31]
Varandas J., Baptista P., Santos J., Martins R., Dias J.: Volus--a visualization system for 3d ultrasound data. Ultrasonics 42, 1--9 (2004), 689--694.
[32]
Viola I., Nylund K., Øye O. K., Ulvang D. M., Gilja O. H., Hauser H.: Illustrated ultrasound for multimodal data interpretation of liver examinations. In Proceedings of VCBM'08 (2008), pp. 125--133.
Index Terms
- HeartPad: real-time visual guidance for cardiac ultrasound
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Published: 26 November 2012
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View all- Kiss GStorve SHaugen BTorp H(2014)Augmented reality based tools for echocardiographic acquisitions2014 IEEE International Ultrasonics Symposium10.1109/ULTSYM.2014.0171(695-698)Online publication date: Sep-2014
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