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Automatic 3D cardiovascular MR segmentation with densely-connected volumetric convnets 1

20th International Conference on Medical Image Computing and computer-Assisted Intervention, MICCAI 2017

作者： Yu, Lequan Cheng, Jie-Zhi Dou, Qi Yang, Xin Chen, Hao Qin, Jing Heng, Pheng-Ann Department of Computer Science and Engineering The Chinese University of Hong Kong Shatin Hong Kong Department of Electrical Engineering Chang Gung University Taoyuan Taiwan Centre for Smart Health School of Nursing The Hong Kong Polytechnic University Kowloon Hong Kong Guangdong Provincial Key Laboratory of Computer Vision and Virtual Reality Technology Shenzhen Institutes of Advanced Technology Chinese Academy of Sciences Shenzhen China

ISBN: (数字)9783319661858

ISBN: (纸本)9783319661841

Automatic and accurate whole-heart and great vessel segmentation from 3D cardiac magnetic resonance (MR) images plays an important role in the computer-assisted diagnosis and treatment of cardiovascular disease. However, this task is very challenging due to ambiguous cardiac borders and large anatomical variations among different subjects. In this paper, we propose a novel densely-connected volumetric convolutional neural network, referred as DenseVoxNet, to automatically segment the cardiac and vascular structures from 3D cardiac MR images. The DenseVoxNet adopts the 3D fully convolutional architecture for effective volume-to-volume prediction. From the learning perspective, our DenseVoxNet has three compelling advantages. First, it preserves the maximum information flow between layers by a densely-connected mechanism and hence eases the network training. Second, it avoids learning redundant feature maps by encouraging feature reuse and hence requires fewer parameters to achieve high performance, which is essential for medical applications with limited training data. Third, we add auxiliary side paths to strengthen the gradient propagation and stabilize the learning process. We demonstrate the effectiveness of DenseVoxNet by comparing it with the state-of-the-art approaches from HVSMR 2016 challenge in conjunction with MICCAI, and our network achieves the best dice coefficient. We also show that our network can achieve better performance than other 3D ConvNets but with fewer parameters. © Springer International Publishing AG 2017.

关键词： Medical applications

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Integrating Artificial Intelligence with Real-time Intracranial EEG Monitoring to Automate Interictal Identification of Seizure Onset Zones in Focal Epilepsy

arXiv

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arXiv 2018年

作者： Varatharajah, Yogatheesan Berry, Brent Cimbalnik, Jan Kremen, Vaclav van Gompel, Jamie Stead, Matt Brinkmann, Benjamin Iyer, Ravishankar Worrell, Gregory Electrical and Computer Engineering University of Illinois UrbanaIL61801 United States Mayo Systems Electrophysiology Laboratory Department of Neurology Mayo Clinic RochesterMN55905 United States Czech Institute of Informatics Robotics and Cybernetics Czech Technical University in Prague Prague 6166 36 Czech Republic Department of Neurosurgery Mayo Clinic RochesterMN55905 United States Department of Physiology & Biomedical Engineering Mayo Clinic RochesterMN55905 United States

An ability to map seizure-generating brain tissue, i.e., the seizure onset zone (SOZ), without recording actual seizures could reduce the duration of invasive EEG monitoring for patients with drug-resistant epilepsy. A widely-adopted practice in the literature is to compare the incidence (events/time) of putative pathological electrophysiological biomarkers associated with epileptic brain tissue with the SOZ determined from spontaneous seizures recorded with intracranial EEG, primarily using a single biomarker. Clinical translation of the previous efforts suffers from their inability to generalize across multiple patients because of (a) the inter-patient variability and (b) the temporal variability in the epileptogenic activity. Here, we report an artificial intelligence-based approach for combining multiple interictal electrophysiological biomarkers and their temporal characteristics as a way of accounting for the above barriers and show that it can reliably identify seizure onset zones in a study cohort of 82 patients who underwent evaluation for drug-resistant epilepsy. Our investigation provides evidence that utilizing the complementary information provided by multiple electrophysiological biomarkers and their temporal characteristics can significantly improve the localization potential compared to previously published single-biomarker incidence-based approaches, resulting in an average area under ROC curve (AUC) value of 0.73 in a cohort of 82 patients. Our results also suggest that recording durations between ninety minutes and two hours are sufficient to localize SOZs with accuracies that may prove clinically relevant. The successful validation of our approach on a large cohort of 82 patients warrants future investigation on the feasibility of utilizing intra-operative EEG monitoring and artificial intelligence to localize epileptogenic brain tissue. Broadly, our study demonstrates the use of artificial intelligence coupled with careful feature engineering in

关键词： Support vector machines

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Outer-Linearization-Based Optimization Algorithm for Decentralized Control Design in Flexure-Linked H-Gantry

Outer-Linearization-Based Optimization Algorithm for Decentr...

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IEEE/ASME International Conference on Advanced Intelligent Mechatronics

作者： Jun Ma Si-Lu Chen Wenyu Liang Xiaocong Li Chek Sing Teo Arthur Tay Abdullah Al Mamun Kok Kiong Tan Department of Electrical and Computer Engineering National University of Singapore Singapore Zhejiang Provincial Key Laboratory of Robotics and Intelligent Manufacturing Equipment Technology Chinese Academy of Sciences Ningbo Zhejiang China Department of Electrical and Computer Engineering National Universit of Singapore Singapore Mechatronics Group Singapore Institute of Manufacturing Technology Singapore

The dual-drive H-gantry (DHG) is widely used for high-speed high-precision Cartesian motion control applications. Compared with the rigid-linked gantry design, the flexure-linked design is able to prevent the damage of the cross-arm because a small degree of rotation angle is allowed. Nevertheless, the flexure-linked design possibly induces the resonance of the gantry because of the chattering of control signals. To maintain the precision tracking of two carriages and minimize the chattering of control efforts, we aim to seek the most suitable flexure joints among the available ones and optimize the decentralized feedback controller parameters under parametric uncertainties. The mechatronic design problem is formulated as an H_2 guaranteed cost control problem. All the stabilizing feedback controller gains are parameterized over a convex set, from here, numerical procedures are developed to obtain the global optimum by means of an outer-linearization-based optimization algorithm. Experiments are carried out and the results successfully validate the optimality and the robustness of the proposed design approach.

关键词： Decentralized control Optimization Uncertainty Feedforward systems Adaptive control Robustness Actuators

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Edgy salient local binary patterns in inter-plane relationship for image retrieval in Diabetic Retinopathy

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Procedia computer Science 2017年 115卷 440-447页

作者： Gajanan M. Galshetwar Laxman M. Waghmare Anil B. Gonde Subrahmanyam Murala Center of Excellence in Signal and Image Processing (COESIP) Department of ECE SGGSIET Nanded Maharashtra 431606 India Computer Vision and Pattern Recognition Laboratory Department of Electrical Engineering IIT Ropar Rupnagar 140001 India

In this paper, a novel approach for content based image retrieval (CBIR) in diabetic retinopathy (DR) is proposed. The concept of salient point selection and inter-plane relationship technique is used. Salient points are selected from edgy image and later using inter-planer relationship, Local Binary Patterns (LBPs) are calculated using the salient point as a center pixel. Our approach enhanced the results as we used color features in combination with LBP features. Experimentation is carried out on MESSIDOR database of 1200 retinal images, proposed approach has average precision of 57.82% as compared to the earlier approach whose average precision is 53.70%.

关键词： Content-Based image retrieval (CBIR) Diabetic Retinopathy (DR) Edgy Salient points Local Binary Patterns (LBPs)

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Sparse-then-Dense Alignment based 3D Map Reconstruction Method for Endoscopic Capsule Robots

arXiv

引用

arXiv 2017年

作者： Turan, Mehmet Pilavci, Yusuf Yigit Ganiyusufoglu, Ipek Araujo, Helder Konukoglu, Ender Sitti, Metin Max Planck Institute for Intelligent Systems Stuttgart Germany Computer Vision Laboratory ETH Zurich Switzerland Robotics Laboratory University of Coimbra Portugal Electrical and Electronics Engineering Middle East Technical University Turkey Computer Science Faculty of Engineering and Natural Sciences Sabanci University Turkey

In the gastrointestinal (GI) tract endoscopy field, ingestible wireless capsule endoscopy is emerging as a novel, minimally invasive diagnostic technology for inspection of the GI tract and diagnosis of a wide range of diseases and pathologies. Since the development of this technology, medical device companies and many research groups have made substantial progress in converting passive capsule endoscopes to robotic active capsule endoscopes which can be controlled by the doctor. However, robotic capsule endoscopy still has some challenges. In particular, the use of such devices to generate a precise and globally consistent three-dimensional (3D) map of the entire inner organ remains an unsolved problem. Such global 3D maps of inner organs would help doctors to detect the location and size of diseased areas more accurately, precisely, and intuitively, thus permitting more accurate and intuitive diagnoses. The proposed 3D reconstruction system is built in a modular fashion including preprocessing, frame stitching, and shading-based 3D reconstruction modules. We propose an efficient scheme to automatically select the key frames out of the huge quantity of raw endoscopic images. Together with a bundle fusion approach that aligns Copyright © 2017, The Authors. All rights reserved.

关键词： Endoscopy

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Magnetic-visual sensor fusion based medical SLAM for endoscopic capsule robot

arXiv

引用

arXiv 2017年

作者： Turan, Mehmet Almalioglu, Yasin Gilbert, Hunter Araujo, Helder Konukoglu, Ender Sitti, Metin Max Planck Institute for Intelligent Systems Stuttgart Germany Computer Vision Laboratory Eth Zurich Computer Engineering Department Bogazici University Louisiana State University Baton RougeLA United States Robotics Laboratory University of Coimbra

A reliable, real-time simultaneous localization and mapping (SLAM) method is crucial for the navigation of actively controlled capsule endoscopy robots. These robots are an emerging, minimally invasive diagnostic and therapeutic technology for use in the gastrointestinal (GI) tract. In this study, we propose a dense, non-rigidly deformable, and real-time map fusion approach for actively controlled endoscopic capsule robot applications. The method combines magnetic and vision based localization, and makes use of frame-to-model fusion and model-to-model loop closure. The performance of the method is demonstrated using an ex-vivo porcine stomach model. Across four trajectories of varying speed and complexity, and across three cameras, the root mean square localization errors range from 0.42 to 1.92 cm, and the root mean square surface reconstruction errors range from 1.23 to 2.39 cm. Copyright © 2017, The Authors. All rights reserved.

关键词： Magnetism

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On active decoupling control for horizontal-lateral direction of hypersonic flight based on HIFOO 21

On active decoupling control for horizontal-lateral directio...

引用

21st AIAA International Space Planes and Hypersonics Technologies Conference, Hypersonics 2017

作者： Ma, Shunjian Zhu, Kai Sun, Mingwei Wang, Zenghui Chen, Zengqiang Dept. of Automation and Intelligent Science Nankai University College of Computer and Control Engineering Tianjin300350 China Beijing Aerospace Technology Institute Tianjin Key Laboratory of Intelligent Robotics Tianjin300350 China Beijing Aerospace Technology Institute Beijing100074 China Department of Electrical and Mining Engineering University of South Africa FL1710 South Africa

ISBN: (数字)9781624104633

ISBN: (纸本)9781624104633

Nowadays, hypersonic flight vehicles are widely studied. Since their high nonlinearity, strong coupling and uncertain factors, the conventional three-channel independent control design method is often unable to work well. In this paper, an active disturbance rejection controller (ADRC) is utilized to cancel internal uncertainties and exogenous disturbances for longitudinal dynamics. Then, the MIMO robust controller is obtained by choosing proper sensitivity functions and weighting functions to reduce horizontal-lateral direction coupling. The conventional H robust controllor is high-order, which is difficult for practitioners to implement. With frequency transformation, both ADRC for the longitudinal dynamics and MIMO robust controller for the horizontal-lateral dynamics are reformed into the static output feedback structure to reduce the high order of controller. Finally, all parameters in the controllers can be optimized by HIFOO (H-Infinity Fixed Order Optimization). The Winged-Cone, a 6-freedom NASA hypersonic vehicle model, is used as a benchmark, and Monte Carlo simulations demonstrate the effectiveness of the proposed method. © 2017, American Institute of Aeronautics and Astronautics Inc, AIAA. All rights reserved.

关键词： Controllers

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Fairness and transmission-aware caching and delivery policies in OFDMA-based HetNets

arXiv

引用

arXiv 2017年

作者： Rezvani, Sepehr Mokari, Nader Javan, Mohammad R. Jorswieck, Eduard A. Department of Electrical and Computer Engineering Tarbiat Modares University Tehran Iran Department of Electrical and Robotics Engineering Shahrood University of Technology Shahrood Iran Dresden University of Technology Communications Laboratory Chair of Communication Theory Dresden Germany

Recently, wireless edge caching has been emerged as a promising technology for future wireless networks to cope with exponentially increasing demands for high data rate and low latency multimedia services by proactively storing contents at the network edge. Here, we aim to design efficient cache placement and delivery strategies for an orthogonal frequency division multiple access (OFDMA)- based cache-enabled heterogeneous cellular network (C-HetNet) which operates in two separated phases: caching phase (CP) and delivery phase (DP). Since guaranteeing fairness among mobile users (MUs) is not well investigated in cache-assisted wireless networks, we first propose two delay-based fairness schemes called proportional fairness (PF) and min-max fairness (MMF). The PF scheme deals with minimizing the total weighted latency of MUs while MMF aims at minimizing the maximum latency among them. In the CP, we propose a novel proactive fairness and transmission-aware cache placement strategy (CPS) corresponding to each target fairness scheme by exploiting the flexible wireless access and backhaul transmission opportunities. Specifically, we jointly perform the allocation of physical resources as storage and radio, and user association to improve the flexibility of the CPSs. Moreover, In the DP of each fairness scheme, an efficient delivery policy is proposed based on the arrival requests of MUs, CSI, and caching status. Numerical assessments demonstrate that our proposed CPSs outperform the total latency of MUs up to 27% compared to the conventional baseline popular *** Codes 90C11 Copyright © 2017, The Authors. All rights reserved.

关键词： Orthogonal frequency division multiplexing

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Adaptive decontamination of the training set: A unified formulation for discriminative visual tracking

Adaptive decontamination of the training set: A unified form...

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2016 IEEE Conference on computer vision and Pattern Recognition, CVPR 2016

作者： Danelljan, Martin Häger, Gustav Khan, Fahad Shahbaz Felsberg, Michael Computer Vision Laboratory Department of Electrical Engineering Linköping University Sweden

ISBN: (纸本)9781467388511

Tracking-by-detection methods have demonstrated competitive performance in recent years. In these approaches, the tracking model heavily relies on the quality of the training set. Due to the limited amount of labeled training data, additional samples need to be extracted and labeled by the tracker itself. This often leads to the inclusion of corrupted training samples, due to occlusions, misalignments and other perturbations. Existing tracking-by-detection methods either ignore this problem, or employ a separate component for managing the training set. We propose a novel generic approach for alleviating the problem of corrupted training samples in tracking-bydetection frameworks. Our approach dynamically manages the training set by estimating the quality of the samples. Contrary to existing approaches, we propose a unified formulation by minimizing a single loss over both the target appearance model and the sample quality weights. The joint formulation enables corrupted samples to be downweighted while increasing the impact of correct ones. Experiments are performed on three benchmarks: OTB-2015 with 100 videos, VOT-2015 with 60 videos, and Temple-Color with 128 videos. On the OTB-2015, our unified formulation significantly improves the baseline, with a gain of 3.8% in mean overlap precision. Finally, our method achieves state-of-the-art results on all three datasets.

关键词： computer vision

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A probabilistic framework for color-based point set registration

A probabilistic framework for color-based point set registra...

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2016 IEEE Conference on computer vision and Pattern Recognition, CVPR 2016

作者： Danelljan, Martin Meneghetti, Giulia Khan, Fahad Shahbaz Felsberg, Michael Computer Vision Laboratory Department of Electrical Engineering Linköping University Sweden

ISBN: (纸本)9781467388511

In recent years, sensors capable of measuring both color and depth information have become increasingly popular. Despite the abundance of colored point set data, stateof-the-art probabilistic registration techniques ignore the available color information. In this paper, we propose a probabilistic point set registration framework that exploits available color information associated with the points. Our method is based on a model of the joint distribution of 3D-point observations and their color information. The proposed model captures discriminative color information, while being computationally efficient. We derive an EM algorithm for jointly estimating the model parameters and the relative transformations. Comprehensive experiments are performed on the Stanford Lounge dataset, captured by an RGB-D camera, and two point sets captured by a Lidar sensor. Our results demonstrate a significant gain in robustness and accuracy when incorporating color information. On the Stanford Lounge dataset, our approach achieves a relative reduction of the failure rate by 78% compared to the baseline. Furthermore, our proposed model outperforms standard strategies for combining color and 3D-point information, leading to state-of-the-art results.

关键词： Color

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