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Breast MRI Radiogenomics: Current Status and Research Implications

JOURNAL OF MAGNETIC RESONANCE IMAGING 2016年第6期43卷 1269-1278页

作者： Grimm, Lars J. Duke Univ Med Ctr Dept Radiol Box 3808 Durham NC 27710 USA

Breast magnetic resonance imaging (MRI) radiogenomics is an emerging area of research that has the potential to directly influence clinical practice. Clinical MRI scanners today are capable of providing excellent temporal and spatial resolution, which allows extraction of numerous imaging features via human extraction approaches or complex computer vision algorithms. Meanwhile, advances in breast cancer genetics research has resulted in the identification of promising genes associated with cancer outcomes. In addition, validated genomic signatures have been developed that allow categorization of breast cancers into distinct molecular subtypes as well as predict the risk of cancer recurrence and response to therapy. Current radiogenomics research has been directed towards exploratory analysis of individual genes, understanding tumor biology, and developing imaging surrogates to genetic analysis with the long-term goal of developing a meaningful tool for clinical care. The background of breast MRI radiogenomics research, image feature extraction techniques, approaches to radiogenomics research, and promising areas of investigation are reviewed.

关键词： MRI breast cancer radiogenomics computer vision algorithms genetics

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Video-guided Camera Control for Target Tracking and Following

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IFAC-PapersOnLine 2019年第34期51卷 176-183页

作者： Gemerek, Jake Ferrari, Silvia Wang, Brian H. Campbell, Mark E. Department of Mechanical and Aerospace Engineering Cornell University IthacaNY United States

This paper considers the problem of controlling a nonholonomic mobile ground robot equipped with an onboard camera characterized by a bounded field-of-view, tasked with detecting and following a potentially moving human target using onboard computing and video processing in real time. computer vision algorithms have been recently shown highly effective at object detection and classification in images obtained by vision sensors. Existing methods typically assume a stationary camera and/or use pre-recorded image sequences that do not provide a causal relationship with future images. The control method developed in this paper seeks to improve the performance of the computer vision algorithms, by planning the robot/camera trajectory relative to the moving target based on the desired size and position of the target in the image plane, without the need to estimate the target's range. The method is tested and validated using a highly realistic and interactive game programming environment, known as Unreal Engine™, that allows for closed-loop simulations of the robot-camera system. Results are further validated through physical experiments using a Clearpath™ Jackal robot equipped with a camera which is capable of following a human target for long time periods. Both simulation and experimental results show that the proposed vision-based controller is capable of stabilizing the target object size and position in the image plane for extended periods of time. © 2019

关键词： Visual servoing Cameras computer vision Image enhancement Object detection Robot programming Robots Target tracking Video signal processing Causal relationships Closed loop simulations computer vision algorithms Physical experiments Robot controls Robot navigation Tracking application vision based controllers

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The analysis of selected orientation methods of architectural objects' scans 13

The analysis of selected orientation methods of architectura...

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Conference on Videometrics, Range Imaging, and Applications XIII

作者： Markiewicz, Jakub S. Kajdewicz, Irmina Zawieska, Dorota Warsaw Univ Technol Dept Photogrammetry Remote Sensing & Spatial Info Fac Geodesy & Cartog PL-00661 Warsaw Poland

ISBN: (纸本)9781628416886

The terrestrial laser scanning is commonly used in different areas, inter alia in modelling architectural objects. One of the most important part of TLS data processing is scans registration. It significantly affects the accuracy of generation of high resolution photogrammetric documentation. This process is time consuming, especially in case of a large number of scans. It is mostly based on an automatic detection and a semi-automatic measurement of control points placed on the object. In case of the complicated historical buildings, sometimes it is forbidden to place survey targets on an object or it may be difficult to distribute survey targets in the optimal way. Such problems encourage the search for the new methods of scan registration which enable to eliminate the step of placing survey targets on the object. In this paper the results of target-based registration method are presented The survey targets placed on the walls of historical chambers of the Museum of King Jan III's Palace at Wilanow and on the walls of ruins of the Bishops Castle in Ilza were used for scan orientation. Several variants of orientation were performed, taking into account different placement and different number of survey marks. Afterwards, during next research works, raster images were generated from scans and the SIFT and SURF algorithms for image processing were used to automatically search for corresponding natural points. The case of utilisation of automatically identified points for TLS data orientation was analysed. The results of both methods for TLS data registration were summarized and presented in numerical and graphical forms.

关键词： automatic TLS registration target-based methods spherical images computer vision algorithms accuracy orthoimages

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FPGA-based Path-planning of High Mobility Rover for Future Planetary Missions

FPGA-based Path-planning of High Mobility Rover for Future P...

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19th IEEE International Conference on Electronics, Circuits, and Systems (ICECS 2012)

作者： Lentaris, G. Diamantopoulos, D. Stamoulias, G. Siozios, K. Soudris, D. Aviles Rodrigalvarez, M. Natl Tech Univ Athens Sch Elect & Comp Engn Athens Greece GMV Adv Space Syst & Technol Madrit Spain

ISBN: (纸本)9781467312608

Work in navigational autonomy for planetary exploration rovers has focused on achieving safe and efficient path-planning through unknown, rocky terrain. computer vision is playing an important role in increasing autonomy of both spacecraft and robotic vehicles, however due to their increased computational complexity, they are rarely implemented onto conventional computing systems. This problem becomes far more severe whenever real-time constraints have also to be considered. This paper addresses progress on rover path planning for high mobility mars rover missions. More specifically, at SPARTAN project, a demonstrator is being developed that meets ESA's specifications for the problem of rover Localization. This problem accounts for the generation of location estimates. This process involves four distinct applications: Imaging, 3D-Reconstruction, Visual Odometry (VO) and Visual Simultaneous Localization and Map reconstruction (SLAM). On supporting these functions we developed a novel HW/SW co-design methodology that extracts parallelism in higher algorithmic level, and thus allows the simultaneous execution of computational intensive kernels on a FPGA device, while the control flow is maintained by a low-performance CPU. Experimental results show that our implementation achieves the scopes of SPARTAN project.

关键词： computer vision algorithms Space Application FPGA implementation High-Performance HW/SW co-design

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Classification of smart video surveillance systems for commercial applications

Classification of smart video surveillance systems for comme...

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IEEE Conference on Advanced Video and Signal Based Surveillance

作者： Sedky, MH Moniri, M Chibelushi, CC

ISBN: (纸本)0780393856

Video surveillance has a large market as the number of installed cameras around us can show. There are immediate commercial needs for smart video surveillance systems that can make use of the existing camera net-work (e.g. CCTV) for more intelligent security systems and to contribute in more applications (beside or) rather than security applications. This work introduces a new classification for smart video surveillance systems depending on their commercial applications. This paper highlights different links between the research and the commercial applications. The work reported here has both research and commercial motivations. Our goals are first to define a generic model of smart video surveillance systems that can meet requirements of strong commercial applications. Our second goal is to categorize different smart video surveillance applications and to relate capabilities of computer vision algorithms to the requirement of commercial application.

关键词： computer vision security surveillance video signal processing commercial applications computer vision algorithms intelligent security systems smart video surveillance systems computer vision video monitoring Video signal processing Accidents,emergencies and safety Security

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An Efficient Approach for Detecting Moving Objects and Deriving Their Positions and Velocities

An Efficient Approach for Detecting Moving Objects and Deriv...

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computer vision Conference (CVC)

作者： Gustaysson, Andreas Malardalen Univ Hgsk Plan 1 S-72220 Vasteras Sweden

ISBN: (纸本)9783030177980;9783030177973

Well-functioning autonomous robot solutions heavily rely on the availability of fast and correct navigation solutions. The presence of dynamic/moving objects in the environment poses a challenge because the risk of collision increases. In order to derive the best and most foreseeing re-routing solutions for cases where the planned route suddenly involves the risk of colliding with a moving object, the robot's navigation system must be provided with information about such objects' positions and velocities. Based on sensor readings providing either 2-dimensional polar range scan or 3-dimensional point cloud data streams, we present an efficient and effective method which detects objects in the environment and derives their positions and velocities. The method has been implemented, based on the Robot Operating System (ROS), and we also present an evaluation of it. It was found that the method results in good accuracy in the position and velocity calculations, a small memory footprint and low CPU usage requirements.

关键词： computer vision algorithms Object detection Robotics ROS

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A local real-time bar detector based on the multiscale Radon transform

A local real-time bar detector based on the multiscale Radon...

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Conference on Real-Time Image Processing and Deep Learning

作者： Oliva-Garcia, Ricardo Gomez-Cardenes, Oscar Marichal-Hernandez, Jose G. Martin-Hernandez, Javier Phillip-Luke, Jonas Rodriguez-Ramos, Jose M. Univ La Laguna Ind Engn Dept ETSI San Cristobal la Laguna 38200 Spain Wooptix SL Av Trinidad 61 San Cristobal la Laguna 38204 Spain

ISBN: (纸本)9781510650817;9781510650800

We propose a local bar-shaped structure detector that works in real time on high-resolution images. It is based on the Radon transform. Specifically in the muti-scale variant, which is especially fast because it works in integer mathematics and does not use interpolation. The Radon transform conventionally works on the whole image, and not locally. In this paper we describe how by stopping at the early stages of the Radon transform we are able to locate structures locally. We also provide an evaluation of the performance of the algorithm running on the CPU, GPU and DSP of mobile devices to process at acquisition time the images coming from the device's camera.

关键词： Bar detector computer vision algorithms Radon Transform Real-time implementations Code bar detector Local detector

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computer based quantification of normal and pathological vocal folds phonatory processes from laryngovideostroboscopy

Computer based quantification of normal and pathological voc...

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3rd International Conference on Innovative Network Systems and Applications (iNetSApp) held in conjunction with Federated Conference on computer Science and Information Systems (FedCSIS)

作者： Kopczynski, Bartosz Strumillo, Pawel Niebudek-Bogusz, Ewa Lodz Univ Technol Inst Elect Ul Wolczanska 211-215 PL-90924 Lodz Poland Nofer Inst Occupat Med Dept Audiol & Phoniatr PL-91348 Lodz Poland

ISBN: (纸本)9788360810668

Medical imaging techniques offer novel visualization and analysis methods of the vocal folds during phonation and automatic computation of indices aiding the phoniatrist in a more precise diagnosis of voice disorders. The aim of this study is to apply computer vision algorithms for qualitative and quantitative analysis of vocal folds' vibrations. Videostroboscopic examinations of the larynx were carried out for 30 patients. Image pre-processing and image segmentation algorithms were applied to compute the glottis area during phonation. The glottovibrograms which are spatio-temporal visualizations of the vibrating vocal folds were also built. The proposed indices allow for a quantitative and comparative analysis of normal and disordered phonatory processes. The conducted pilot study has confirmed the validity of the computer aided imaging methods for the qualitative and quantitative analysis of the videostroboscopic images of the phonatory motions of the vocal folds.

关键词： computer vision image segmentation medical image processing video signal processing analysis methods automatic index computation comparative analysis computer aided imaging methods computer based quantification computer vision algorithms disordered phonatory process glottis area glottovibrograms image preprocessing laryngovideostroboscopy larynx medical imaging techniques normal phonatory process normal vocal fold phonatory process pathological vocal fold phonatory process phonation phonatory motions qualitative analysis quantitative analysis spatio-temporal visualizations videostroboscopic images visualization methods vocal fold vibrations voice disorder diagnosis Algorithm design and analysis Cameras computers Image segmentation Larynx Pathology Videos image segmentation Vocal Cords Larynx images computers Phonation computer vision Algorithm design and analysis visualization methods QUANTITATIVE ANALYSIS Video signal processing Medical image processing Videotapes Cameras pathology

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Computational Complexity Optimization of Vehicle Video-Recognition Algorithm Using the Virtual Detectors Method

Computational Complexity Optimization of Vehicle Video-Recog...

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2024 Systems of Signal Synchronization, Generating and Processing in Telecommunications, SYNCHROINFO 2024

作者： Kuteynikov, Ivan Yashina, Marina Department of Higher Mathematics Moscow Russia Moscow Technical University of Communications and Informatics Moscow Moscow Russia Moscow Russia

ISBN: (纸本)9798350373448

The paper presents the research of computational complexity optimization of a virtual detector method for video-based vehicle recognition. This method enables a more flexible and adaptive analytical research and optimizes the resource utilization. In addition, the optimization of the computational complexity of the video recognition algorithm required to improve accuracy and speed is investigated. This approach allows to significantly reduce the load on computational resources and ensure the accuracy and efficiency of vehicle recognition even when the frame rate is reduced. The paper presents a system for monitoring the dynamics of traffic flows based on the method of virtual detectors - «ViDeS» (Virtual Detectors System) for which the analysis of recognition efficiency depending on the frame rate is conducted. The developed software allows to increase the efficiency of traffic flow vehicle recognition © 2024 IEEE.

关键词： adaptive metrics computer vision algorithms data analysis vehicle counting virtual detector method

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Visual Features for Improving Endoscopic Bleeding Detection Using Convolutional Neural Networks

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SENSORS 2023年第24期23卷 9717-9717页

作者： Brzeski, Adam Dziubich, Tomasz Krawczyk, Henryk Gdańsk Univ Technol Fac Elect Telecommun & Informat PL-80233 Gdansk Poland

The presented paper investigates the problem of endoscopic bleeding detection in endoscopic videos in the form of a binary image classification task. A set of definitions of high-level visual features of endoscopic bleeding is introduced, which incorporates domain knowledge from the field. The high-level features are coupled with respective feature descriptors, enabling automatic capture of the features using image processing methods. Each of the proposed feature descriptors outputs a feature activation map in the form of a grayscale image. Acquired feature maps can be appended in a straightforward way to the original color channels of the input image and passed to the input of a convolutional neural network during the training and inference steps. An experimental evaluation is conducted to compare the classification ROC AUC of feature-extended convolutional neural network models with baseline models using regular color image inputs. The advantage of feature-extended models is demonstrated for the Resnet and VGG convolutional neural network architectures.

关键词： machine learning artificial intelligence computer vision algorithms convolutional neural networks medical image analysis

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