Left ventricle myocardial border detection in three-dimensional intracardiac ultrasound images

1997 ◽  
Author(s):  
Weidong Liang ◽  
Prapti Kanani ◽  
John Allan ◽  
Richard Kerber ◽  
Charles R. McKay ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Three Dimensional ◽  
Ultrasound Images ◽  
Border Detection ◽  
Intracardiac Ultrasound ◽  
Myocardial Border

scholarly journals Deep learning‐based carotid media‐adventitia and lumen‐intima boundary segmentation from three‐dimensional ultrasound images

2019 ◽  
Vol 46 (7) ◽  
pp. 3180-3193 ◽  
Author(s):  
Ran Zhou ◽  
Aaron Fenster ◽  
Yujiao Xia ◽  
J. David Spence ◽  
Mingyue Ding
Keyword(s):  
Deep Learning ◽  
Three Dimensional ◽  
Ultrasound Images

Three-dimensional active shape model matching for left ventricle segmentation in cardiac CT

2003 ◽  
Author(s):  
Hans C. van Assen ◽  
Rob J. van der Geest ◽  
Mikhail G. Danilouchkine ◽  
Hildo J. Lamb ◽  
Johan H. C. Reiber ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Cardiac Ct ◽  
Three Dimensional ◽  
Active Shape Model ◽  
Model Matching ◽  
Shape Model ◽  
Active Shape ◽  
Ventricle Segmentation

Robotic motion compensation for bone movement, using ultrasound images

2015 ◽  
Vol 42 (5) ◽  
pp. 466-474 ◽  
Author(s):  
P.M.B. Torres ◽  
P. J. S. Gonçalves ◽  
J.M.M. Martins
Keyword(s):  
Motion Compensation ◽  
Optical Measurement ◽  
Three Dimensional ◽  
Point Clouds ◽  
Robotic System ◽  
Ultrasound Images ◽  
Bone Drilling ◽  
Content Type ◽  
3D Point Clouds ◽  
Robotic Motion

Purpose – The purpose of this paper is to present a robotic motion compensation system, using ultrasound images, to assist orthopedic surgery. The robotic system can compensate for femur movements during bone drilling procedures. Although it may have other applications, the system was thought to be used in hip resurfacing (HR) prosthesis surgery to implant the initial guide tool. The system requires no fiducial markers implanted in the patient, by using only non-invasive ultrasound images. Design/methodology/approach – The femur location in the operating room is obtained by processing ultrasound (USA) and computer tomography (CT) images, obtained, respectively, in the intra-operative and pre-operative scenarios. During surgery, the bone position and orientation is obtained by registration of USA and CT three-dimensional (3D) point clouds, using an optical measurement system and also passive markers attached to the USA probe and to the drill. The system description, image processing, calibration procedures and results with simulated and real experiments are presented and described to illustrate the system in operation. Findings – The robotic system can compensate for femur movements, during bone drilling procedures. In most experiments, the update was always validated, with errors of 2 mm/4°. Originality/value – The navigation system is based entirely on the information extracted from images obtained from CT pre-operatively and USA intra-operatively. Contrary to current surgical systems, it does not use any type of implant in the bone to track the femur movements.

scholarly journals Long-term prognostic significance of three-dimensional echocardiographic parameters of the left ventricle and left atrium

2009 ◽  
Vol 11 (3) ◽  
pp. 250-256 ◽  
Author(s):  
S. Caselli ◽  
E. Canali ◽  
M. L. Foschi ◽  
D. Santini ◽  
E. Di Angelantonio ◽  
...  
Keyword(s):  
Left Ventricle ◽  
Left Atrium ◽  
Prognostic Significance ◽  
Three Dimensional ◽  
Echocardiographic Parameters

Real-time nonlinear filtration for three-dimensional ultrasound images distorted by noise

2006 ◽  
Vol 51 (6) ◽  
pp. 304-310 ◽  
Author(s):  
V. F. Kravchenko ◽  
V. I. Ponomaryov ◽  
V. I. Pustovoĭt ◽  
R. Sansores-Pech
Keyword(s):  
Real Time ◽  
Three Dimensional ◽  
Nonlinear Filtration ◽  
Ultrasound Images

scholarly journals Minimally interactive placenta segmentation from three-dimensional ultrasound images

2020 ◽  
Vol 7 (01) ◽  
pp. 1
Author(s):  
Ipek Oguz ◽  
Natalie Yushkevich ◽  
Alison Pouch ◽  
Baris U. Oguz ◽  
Jiancong Wang ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Ultrasound Images

scholarly journals Automatic border detection of intravascular ultrasound images

1996 ◽  
Vol 27 (2) ◽  
pp. 240
Author(s):  
Stephen P. Wiet ◽  
Stuart A. Greenfield ◽  
Reena Sinha ◽  
Gorav Ailawadi ◽  
Michael J. Vonesh ◽  
...  
Keyword(s):  
Intravascular Ultrasound ◽  
Ultrasound Images ◽  
Border Detection
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