Computer-Assisted 3-D Ultrasound Probe Placement for Emergency Healthcare Applications

In this paper, a new computer-assisted ultrasound probe placement system is introduced to guide paramedics and first responders to conduct abdominal ultrasound imaging for diagnosing trauma patients in emergency situations where specialists are not present. Recently, telesonography has been employed to supervise paramedics by remote experts to perform ultrasound scan for triaging, although its utility is limited by unavailability of fast internet connectivity in remote regions. In the proposed solution of this paper, a paramedic is first instructed to place the ultrasound probe on an initial placement for imaging an organ of interest. Then, a three-dimensional (3-D) ultrasound image is acquired and processed to determine the organ's shape misalignment with respect to a reference alignment. Afterward, the organ's shape misalignment is used to estimate the probe misalignment, and then, a probe placement command is generated to guide the paramedic. This process iterates until a correct organ's view of interest is obtained. As the advantage of the proposed solution over the existing technique, the proposed solution does not require a fast Internet connectivity and a dedicated remote specialist to conduct ultrasound imaging by a paramedic. The utility of the proposed solution is evaluated for a case study on the right upper quadrant (RUQ) view, which has a paramount importance in triaging trauma patients. Accuracy and robustness of the proposed solution is verified using actual and simulated 3-D ultrasound images of the RUQ view.

[1]  Stefan Wesarg,et al.  Automated Kidney Detection and Segmentation in 3D Ultrasound , 2013, CLIP.

[2]  Tony F. Chan,et al.  Active contours without edges , 2001, IEEE Trans. Image Process..

[3]  Konstantinos N. Plataniotis,et al.  Shape-based kidney detection and segmentation in three-dimensional abdominal ultrasound images , 2014, 2014 36th Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

[4]  J Varandas,et al.  VOLUS--a visualization system for 3D ultrasound data. , 2004, Ultrasonics.

[5]  David Shan-Hill Wong,et al.  Fault Detection Based on Statistical Multivariate Analysis and Microarray Visualization , 2010, IEEE Transactions on Industrial Informatics.

[6]  Herman Morchel,et al.  Development and evaluation of a novel, real time mobile telesonography system in management of patients with abdominal trauma: study protocol , 2012, BMC Emergency Medicine.

[7]  Hamid Shokoohi,et al.  Horizontal subxiphoid landmark optimizes probe placement during the Focused Assessment with Sonography for Trauma ultrasound exam , 2012, European journal of emergency medicine : official journal of the European Society for Emergency Medicine.

[8]  Yutaka Satoh,et al.  Using selective correlation coefficient for robust image registration , 2003, Pattern Recognit..

[9]  Carl-Fredrik Westin,et al.  Oriented Speckle Reducing Anisotropic Diffusion , 2007, IEEE Transactions on Image Processing.

[10]  Paul J. Besl,et al.  A Method for Registration of 3-D Shapes , 1992, IEEE Trans. Pattern Anal. Mach. Intell..

[11]  W. Brent Lindquist,et al.  Image Thresholding by Indicator Kriging , 1999, IEEE Trans. Pattern Anal. Mach. Intell..

[12]  David J. Ketcham Real-Time Image Enhancement Techniques , 1976, Other Conferences.

[13]  E. R. Smith,et al.  Tele-ultrasound and paramedics: real-time remote physician guidance of the Focused Assessment With Sonography for Trauma examination. , 2011, The American journal of emergency medicine.

[14]  Chia-Hung Wang,et al.  Optimal multi-level thresholding using a two-stage Otsu optimization approach , 2009, Pattern Recognit. Lett..

[15]  Geert Deconinck,et al.  Residential Electrical Load Model Based on Mixture Model Clustering and Markov Models , 2013, IEEE Transactions on Industrial Informatics.

[16]  Kilian M. Pohl,et al.  Image Registration Assists Novice Operators in Ultrasound Assessment of Abdominal Trauma , 2008, MMVR.

[17]  Ghassan Hamarneh,et al.  Active Learning for Interactive 3D Image Segmentation , 2011, MICCAI.

[18]  Ming Yang,et al.  Separable Beamforming For 3-D Medical Ultrasound Imaging , 2015, IEEE Transactions on Signal Processing.

[19]  F B Knotts,et al.  Emergency physician use of ultrasonography in blunt abdominal trauma. , 1996, Academic emergency medicine : official journal of the Society for Academic Emergency Medicine.

[20]  Ayman El-Baz,et al.  State-of-the-Art Medical Image Registration Methodologies: A Survey , 2011 .

[21]  Stergios Stergiopoulos,et al.  Portable 3D/4D Ultrasound Diagnostic Imaging System , 2010 .

[22]  Piero Tortoli,et al.  Multi-Transmit Beam Forming for Fast Cardiac Imaging—Experimental Validation and In Vivo Application , 2014, IEEE Transactions on Medical Imaging.

[23]  Chad G Ball,et al.  Scandinavian Journal of Trauma, Resuscitation and Emergency Medicine Clinician Performed Resuscitative Ultrasonography for the Initial Evaluation and Resuscitation of Trauma , 2009 .