Applications of Image Processing in Laparoscopic Surgeries

2017 ◽  
pp. 317-343
Author(s):  
Toktam Khatibi ◽  
Mohammad Mehdi Sepehri ◽  
Pejman Shadpour ◽  
Seyed Hessameddin Zegordi
Keyword(s):  
Image Processing ◽  
Soft Tissue ◽  
Video Processing ◽  
Position Estimation ◽  
Surgical Instrument ◽  
Tissue Segmentation ◽  
Detection And Tracking ◽  
Video Frames ◽  
High Level ◽  
Laparoscopic Videos

Laparoscopy is a minimally-invasive surgery using a few small incisions on the patient's body to insert the tools and telescope and conduct the surgical operation. Laparoscopic video processing can be used to extract valuable knowledge and help the surgeons. We discuss the present and possible future role of processing laparoscopic videos. The various applications are categorized for image processing algorithms in laparoscopic surgeries including preprocessing video frames by laparoscopic image enhancement, telescope related applications (telescope position estimation, telescope motion estimation and compensation), surgical instrument related applications (surgical instrument detection and tracking), soft tissue related applications (soft tissue segmentation and deformation tracking) and high level applications such as safe actions in laparoscopic videos, summarization of laparoscopic videos, surgical task recognition and extracting knowledge using fusion techniques. Some different methods have been proposed previously for each of the mentioned applications using image processing.

Applications of Image Processing in Laparoscopic Surgeries

2018 ◽  
pp. 1518-1544
Author(s):  
Toktam Khatibi ◽  
Mohammad Mehdi Sepehri ◽  
Pejman Shadpour ◽  
Seyed Hessameddin Zegordi
Keyword(s):  
Image Processing ◽  
Soft Tissue ◽  
Video Processing ◽  
Position Estimation ◽  
Surgical Instrument ◽  
Tissue Segmentation ◽  
Detection And Tracking ◽  
Video Frames ◽  
High Level ◽  
Laparoscopic Videos

Laparoscopy is a minimally-invasive surgery using a few small incisions on the patient's body to insert the tools and telescope and conduct the surgical operation. Laparoscopic video processing can be used to extract valuable knowledge and help the surgeons. We discuss the present and possible future role of processing laparoscopic videos. The various applications are categorized for image processing algorithms in laparoscopic surgeries including preprocessing video frames by laparoscopic image enhancement, telescope related applications (telescope position estimation, telescope motion estimation and compensation), surgical instrument related applications (surgical instrument detection and tracking), soft tissue related applications (soft tissue segmentation and deformation tracking) and high level applications such as safe actions in laparoscopic videos, summarization of laparoscopic videos, surgical task recognition and extracting knowledge using fusion techniques. Some different methods have been proposed previously for each of the mentioned applications using image processing.

scholarly journals A new method for vehicles detection and tracking using information and image processing

2021 ◽  
Vol 11 (6) ◽  
pp. 4942
Author(s):  
Mazouzi Amine ◽  
Kerfa Djoudi ◽  
Ismail Rakip Karas
Keyword(s):  
Image Processing ◽  
Mathematical Morphology ◽  
New Method ◽  
Video Sequences ◽  
Detection Level ◽  
Low Level ◽  
Detection And Tracking ◽  
High Level

<span lang="EN-US">In this article, a new method of vehicles detecting and tracking is presented: A thresholding followed by a mathematical morphology treatment are used. The tracking phase uses the information about a vehicle. An original labeling is proposed in this article. It helps to reduce some artefacts that occur at the detection level. The main contribution of this article lies in the possibility of merging information of low level (detection) and high level (tracking). In other words, it is shown that many artefacts resulting from image processing (low level) can be detected, and eliminated thanks to the information contained in the labeling (high level). The proposed method has been tested on many video sequences and examples are given illustrating the merits of our approach.</span>

Vision System Based Lane Keeping Assistance Evaluated in a Hardware-in-the-Loop Simulator

2010 ◽  
Author(s):  
Fuat Cos¸kun ◽  
O¨zgu¨r Tuncer ◽  
Elif Karslıgil ◽  
Levent Gu¨venc¸
Keyword(s):  
Image Processing ◽  
Real Time ◽  
Lane Detection ◽  
Assistance System ◽  
Hardware In The Loop ◽  
Vehicle Model ◽  
Detection And Tracking ◽  
Video Frames ◽  
Assistance Systems ◽  
Lane Keeping

Lane keeping assistance systems help the driver in following the lane centerline. While lane keeping assistance systems are available in some mass production vehicles, they have not found widespread use and are not as common as ESP or ACC at the moment. Lane keeping assistance systems still need further development. Previously available systems have to be continuously adapted to newer vehicle models and fully tested after this adaptation. An image processing algorithm for lane detection and tracking, a lane keeping assistance controller design and a real time hardware-in-the-loop (HiL) simulator developed for testing the designed lane keeping assistance system are therefore presented in this paper. The high fidelity, high order, realistic and nonlinear vehicle model in Carmaker HiL runs as software in a real time simulation on a dSpace compact simulator with the DS1005 and DS2210 boards. A PC is used for processing video frames coming from an in-vehicle camera pointed towards the road ahead. Lane detection and tracking computations including fitting of composite Bezier curves to curved lanes are carried out on this PC. In the present setup, the camera used is a virtual camera attached to the virtual vehicle in Carmaker and provides video frames from the Carmaker animation screen. A dSpace microautobox is available for obtaining the lane data from the PC and the Carmaker vehicle data from the dSpace compact simulator and calculating the required steering actions and sending them to the Carmaker vehicle model. The lane keeping controller is designed in the Matlab toolbox COMES using parameter space techniques. The motivation behind this approach is to develop the lane keeping assistance system as much as possible in a laboratory hardware-in-the-loop setting before time consuming, expensive and potentially dangerous road testing. Lane detection, tracking and curved lane fit results, hardware-in-the-loop simulation results of the lane keeping controller with the image processing system are are used to demonstrate the effectiveness of the proposed method.

Modern Technology for Image processing and Computer vision -A Review

2018 ◽  
Vol 1 (2) ◽  
pp. 17-23
Author(s):  
Takialddin Al Smadi
Keyword(s):  
Image Processing ◽  
Computer Vision ◽  
Augmented Reality ◽  
Video Compression ◽  
Video Processing ◽  
Vision System ◽  
Citrus Fruit ◽  
Modern Technology ◽  
Image And Video Processing ◽  
Depth Video

This survey outlines the use of computer vision in Image and video processing in multidisciplinary applications; either in academia or industry, which are active in this field.The scope of this paper covers the theoretical and practical aspects in image and video processing in addition of computer vision, from essential research to evolution of application.In this paper a various subjects of image processing and computer vision will be demonstrated ,these subjects are spanned from the evolution of mobile augmented reality (MAR) applications, to augmented reality under 3D modeling and real time depth imaging, video processing algorithms will be discussed to get higher depth video compression, beside that in the field of mobile platform an automatic computer vision system for citrus fruit has been implemented ,where the Bayesian classification with Boundary Growing to detect the text in the video scene. Also the paper illustrates the usability of the handed interactive method to the portable projector based on augmented reality.   © 2018 JASET, International Scholars and Researchers Association

scholarly journals GPU-Enabled Serverless Workflows for Efficient Multimedia Processing

2021 ◽  
Vol 11 (4) ◽  
pp. 1438
Author(s):  
Sebastián Risco ◽  
Germán Moltó
Keyword(s):  
Video Processing ◽  
Cost Effective ◽  
Multimedia Processing ◽  
Computing Services ◽  
Video Frames ◽  
Open Source Framework ◽  
Cloud Infrastructures ◽  
Aws Lambda ◽  
Runtime Environments

Serverless computing has introduced scalable event-driven processing in Cloud infrastructures. However, it is not trivial for multimedia processing to benefit from the elastic capabilities featured by serverless applications. To this aim, this paper introduces the evolution of a framework to support the execution of customized runtime environments in AWS Lambda in order to accommodate workloads that do not satisfy its strict computational requirements: increased execution times and the ability to use GPU-based resources. This has been achieved through the integration of AWS Batch, a managed service to deploy virtual elastic clusters for the execution of containerized jobs. In addition, a Functions Definition Language (FDL) is introduced for the description of data-driven workflows of functions. These workflows can simultaneously leverage both AWS Lambda for the highly-scalable execution of short jobs and AWS Batch, for the execution of compute-intensive jobs that can profit from GPU-based computing. To assess the developed open-source framework, we executed a case study for efficient serverless video processing. The workflow automatically generates subtitles based on the audio and applies GPU-based object recognition to the video frames, thus simultaneously harnessing different computing services. This allows for the creation of cost-effective highly-parallel scale-to-zero serverless workflows in AWS.

scholarly journals Zebrafish automatic monitoring system for conditioning and behavioral analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Marta de Oliveira Barreiros ◽  
Felipe Gomes Barbosa ◽  
Diego de Oliveira Dantas ◽  
Daniel de Matos Luna dos Santos ◽  
Sidarta Ribeiro ◽  
...  
Keyword(s):  
Video Processing ◽  
Red Light ◽  
Automatic Monitoring ◽  
Automated System ◽  
Control Group ◽  
Automatic Monitoring System ◽  
Fish Schools ◽  
Detection And Tracking ◽  
Evaluation Strategies ◽  
Light Stimuli

AbstractStudies using zebrafish (Danio rerio) in neuro-behavioural research are growing. Measuring fish behavior by computational methods is one of the most efficient ways to avoid human bias in experimental analyses, extending them to various approaches. Sometimes, thorough analyses are difficult to do, as fish can behave unpredictably during an experimental strategy. However, the analyses can be implemented in an automated way, using an online strategy and video processing for a complete assessment of the zebrafish behavior, based on the detection and tracking of fish during an activity. Here, a fully automatic conditioning and detailed analysis of zebrafish behavior is presented. Microcontrolled components were used to control the delivery of visual and sound stimuli, in addition to the concise amounts of food after conditioned stimuli for adult zebrafish groups in a conventional tank. The images were captured and processed for automatic detection of the fish, and the training of the fish was done in two evaluation strategies: simple and complex. In simple conditioning, the zebrafish showed significant responses from the second attempt, learning that the conditioned stimulus was a predictor of food presentation in a specific space of the tank, where the food was dumped. When the fish were subjected to two stimuli for decision-making in the food reward, the zebrafish obtained better responses to red light stimuli in relation to vibration. The behavior change was clear in stimulated fish in relation to the control group, thus, the distances traveled and the speed were greater, while the polarization was lower in stimulated fish. This automated system allows for the conditioning and assessment of zebrafish behavior online, with greater stability in experiments, and in the analysis of the behavior of individual fish or fish schools, including learning and memory studies.

Mechanisms of Soft Tissue Injury

2021 ◽  
Author(s):  
Oneida A. Arosarena ◽  
Issam N. Eid
Keyword(s):  
Soft Tissue ◽  
Tissue Injury ◽  
Visual Fields ◽  
Soft Tissue Injury ◽  
Soft Tissue Injuries ◽  
Wound Management ◽  
Facial Soft Tissue ◽  
Tissue Injuries ◽  
Free Closure ◽  
High Level

AbstractSoft tissue trauma to the face is challenging to manage due to functional and aesthetic concerns. Management requires careful regional considerations to maintain function such as visual fields and oral competence in periorbital and perioral injuries, respectively. Basic wound management principles apply to facial soft tissue injuries including copious irrigation and tension-free closure. There is no consensus and high-level evidence for antibiotic prophylaxis especially in various bite injuries. Ballistic injuries and other mechanisms are briefly reviewed. Scar revision for soft tissue injuries can require multiple procedures and interventions. Surgery as well as office procedures such as resurfacing with lasers can be employed and will be reviewed.

A Vision-Based Gap Detection Method during the Placement of Large-Scale Composite Structures

2011 ◽  
Vol 186 ◽  
pp. 11-15
Author(s):  
Li Cao ◽  
Wen Chen ◽  
Jun Xiao
Keyword(s):  
Image Processing ◽  
Video Processing ◽  
Composite Structures ◽  
Large Scale ◽  
Low Cost ◽  
High Quality ◽  
Detection Technology ◽  
Gap Measurement ◽  
Automatic Placement ◽  
On Line

Video processing technology is regarded as a low-cost detection technology in complex environment. Because the placement layer is thin and the surface is complex that causes high detection error and high cost in laser measurement. Two problems must be solved before using it in large-scale composite structures automatic placement. One is to obtain the high-quality and stable image, and the other is to improve efficiency of image processing. In this paper, a method obtaining the high quality placement gap images was studied. It made use of the optical characteristics of composite material’s surface texture. And some parameters were determined by experiments. To reduce the calculation cost of image processing, a placement gap measurement method based on line scanning was also proposed here. The method was effective in our detection experiments on an actual workpiece.

scholarly journals AN OPTIMIZED SURF-BASED FIRE AND SMOKE DETECTION SYSTEM USING IMAGE PROCESSING FROM SURVEILLANCE VIDEO.

2020 ◽  
Vol 9 (10) ◽  
pp. 86-96
Keyword(s):  
Image Processing ◽  
Feature Extraction ◽  
Feature Selection ◽  
Digital Image Processing ◽  
Digital Image ◽  
Optimization Approach ◽  
Surveillance Video ◽  
Smoke Detection ◽  
Video Frames ◽  
Optimal Feature

Over the last decades, digital image processing based fire and smoke detection have been improving steadily to provide a more accurate detection results in the area of surveillance security system. Detection of the fire and smoke from the surveillance videos is very challenging task due to the complex structural properties of the video frames or images and need improvisation in the existing work by utilization of feature selection or optimization approach to select on optimal feature according to the fire and smoke. A research based on the combination of various feature extraction techniques with feature selection approach for fire and smoke detection has been presented in this paper. In this research, we develop Fire and Smoke Detection (FSD) system using digital image processing with the concept of Speed up Robust Feature (SURF) along with the Intelligent Water Drops (IWD) as a feature selection and optimization algorithm. Here, Artificial Neural Network (ANN) is used as an Artificial Intelligence (AI) technique with that helps to select a set of optimal feature from the extracted by SURF descriptor from the video frames. By utilizing the concept of optimized ANN, the accuracy of proposed FSD system is increases in terms of detection accuracy and with minimum percentage of error. At last, the performance of the FSD system is calculated to validate the model and this shows that it is possible to use IWD with SURF as a feature extraction technique in order to detect the fire or smoke form the surveillance video with minimum error rate and the simulation results clearly show the effectiveness of proposed FSD system

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