A Real-time Needle Tracking Algorithm with First-frame Linear Structure Removing in 2D Ultrasound-guided Prostate Therapy*

Objective. The objective is to explore the clinical application value of ultrasound long- and short-axis planar technology in real-time guided puncture in minimally invasive percutaneous nephrology. Methods. The clinical data of 80 patients undergoing real-time ultrasound-guided minimally invasive percutaneous nephrolithotomy from September 2018 to October 2019 were analyzed. The patients were randomly divided into 2 groups with different ultrasound-guided puncture techniques, long-axis in-plane technique and short-axis out-of-plane technique. Results. Minimally invasive percutaneous nephrolithotomies under real-time ultrasound guidance were successfully completed in both groups of patients. The success rate of the first puncture in the short-axis out-of-plane group was significantly higher than that in the long-axis in-plane group, and the differences were statistically significant ( P <.05); the total puncture time in the short-axis out-of-plane group was significantly less than the long-axis in-plane group, and the differences were statistical significance ( P <.05); there was no significant difference in the single-stage stone removal rate, total percutaneous renal channels, total hospital stay, and rate of complications by the Clavien classification between the 2 groups ( P > .05). Conclusion. Ultrasound long-axis and short-axis planar technologies can achieve good clinical application results in real-time guided puncture to establish percutaneous renal channels during minimally invasive percutaneous nephrolithotomy. Compared with the long-axis in-plane technique, the short-axis out-of-plane technique can shorten the puncture time and improve the success rate of the first puncture.

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Exploring genomes with a game engine

Faraday Discussions ◽

10.1039/c3fd00152k ◽

2014 ◽

Vol 169 ◽

pp. 443-453 ◽

Cited By ~ 3

Author(s):

Jeremiah J. Shepherd ◽

Lingxi Zhou ◽

William Arndt ◽

Yan Zhang ◽

W. Jim Zheng ◽

...

Keyword(s):

Real Time ◽

Video Game ◽

Linear Structure ◽

Structural Data ◽

Game Engine ◽

3D Genome ◽

Genome Viewer ◽

A Genome ◽

Visualization Techniques ◽

Insight Into

More and more evidence indicates that the 3D conformation of eukaryotic genomes is a critical part of genome function. However, due to the lack of accurate and reliable 3D genome structural data, this information is largely ignored and most of these studies have to use information systems that view the DNA in a linear structure. Visualizing genomes in real time 3D can give researchers more insight, but this is fraught with hardware limitations since each element contains vast amounts of information that cannot be processed on the fly. Using a game engine and sophisticated video game visualization techniques enables us to construct a multi-platform real-time 3D genome viewer. The game engine-based viewer achieves much better rendering speed and can handle much larger amounts of data compared to our previous implementation using OpenGL. Combining this viewer with 3D genome models from experimental data could provide unprecedented opportunities to gain insight into the conformation–function relationships of a genome.

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An image-based feature tracking algorithm for real-time measurement of clad height

Machine Vision and Applications ◽

10.1007/s00138-006-0066-7 ◽

2007 ◽

Vol 18 (6) ◽

pp. 343-354 ◽

Cited By ~ 29

Author(s):

Mehrdad Iravani-Tabrizipour ◽

Ehsan Toyserkani

Keyword(s):

Real Time ◽

Feature Tracking ◽

Time Measurement ◽

Tracking Algorithm ◽

Real Time Measurement

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Field Assessment of Camera Based Drilling Dynamics

10.2118/204634-ms ◽

2021 ◽

Author(s):

Alexis Koulidis ◽

Mohamed Abdullatif ◽

Ahmed Galal Abdel-Kader ◽

Mohammed-ilies Ayachi ◽

Shehab Ahmed ◽

...

Keyword(s):

Neural Network ◽

Object Detection ◽

Real Time ◽

Tracking Algorithm ◽

Interest Points ◽

Stick Slip ◽

Detection Algorithms ◽

Point Tracking ◽

Surface Data ◽

Field Assessment

Abstract Surface data measurement and analysis are an established mean of detecting drillstring low-frequency torsional vibration or stick-slip. The industry has also developed models that link surface torque and downhole drill bit rotational speed. Cameras provide an alternative noninvasive approach to existing wired/wireless sensors used to gather such surface data. The results of a preliminary field assessment of drilling dynamics utilizing camera-based drillstring monitoring are presented in this work. Detection and timing of events from the video are performed using computer vision techniques and object detection algorithms. A real-time interest point tracker utilizing homography estimation and sparse optical flow point tracking is deployed. We use a fully convolutional deep neural network trained to detect interest points and compute their accompanying descriptors. The detected points and descriptors are matched across video sequences and used for drillstring rotation detection and speed estimation. When the drillstring's vibration is invisible to the naked eye, the point tracking algorithm is preceded with a motion amplification function based on another deep convolutional neural network. We have clearly demonstrated the potential of camera-based noninvasive approaches to surface drillstring dynamics data acquisition and analysis. Through the application of real-time object detection algorithms on rig video feed, surface events were detected and timed. We were also able to estimate drillstring rotary speed and motion profile. Torsional drillstring modes can be identified and correlated with drilling parameters and bottomhole assembly design. A novel vibration array sensing approach based on a multi-point tracking algorithm is also proposed. A vibration threshold setting was utilized to enable an additional motion amplification function providing seamless assessment for multi-scale vibration measurement. Cameras were typically devices to acquire images/videos for offline automated assessment (recently) or online manual monitoring (mainly), this work has shown how fog/edge computing makes it possible for these cameras to be "conscious" and "intelligent," hence play a critical role in automation/digitalization of drilling rigs. We showcase their preliminary application as drilling dynamics and rig operations sensors in this work. Cameras are an ideal sensor for a drilling environment since they can be installed anywhere on a rig to perform large-scale live video analytics on drilling processes.

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