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检索条件"任意字段=Conference on Visualization in Biomedical Computing"

共 894 条记录，以下是461-470 订阅

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A novel 1-gram insect based device measuring visual motion along 5 optical directions

A novel 1-gram insect based device measuring visual motion a...

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10th IEEE conference on Sensors

作者： Roubieu, Frederic L. Expert, Fabien Boyron, Marc Fuschlock, Benoit-Jeremy Viollet, Stephane Ruffier, Franck CNRS Inst Movement Sci Biorobot Dpt F-75700 Paris France

ISBN: (纸本)9781424492893

Autopilots for micro aerial vehicles (MAVs) with a maximum permissible avionic payload of only a few grams need lightweight, low-power sensors to be able to navigate safely when flying through unknown environments. To meet these demanding specifications, we developed a simple functional model for an Elementary Motion Detector (EMD) circuit based on the common housefly's visual system. During the last two decades, several insect-based visual motion sensors have been designed and implemented on various robots, and considerable improvements have been made in terms of their mass, size and power consumption. The new lightweight visual motion sensor presented here generates 5 simultaneous neighboring measurements of the 1-D angular speed of a natural scene within a measurement range of more than one decade [25 degrees/s;350 degrees/s]. Using a new sensory fusion method consisting in computing the median value of the 5 local motion units, we ended up with a more robust, more accurate and more frequently refreshed measurement of the 1-D angular speed.

关键词： biomedical optical imaging Lenses Motion measurement Optical sensors Sensor phenomena and characterization visualization

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Multimodal image collection summarization using non-negative matrix factorization

Multimodal image collection summarization using non-negative...

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Colombian conference on computing (CCC)

作者： Jorge E. Camargo Fabio A. González Bioingenium Research Group Universidad Nacional de Colombia Colombia

The huge amount of biomedical images that are produced every day require of suitable methods to access them in an efficient and effective way. Although there has been an important development in methods to search large information repositories, these methods have been mainly focused on text data, and less work has been devoted to non-text data such as images and video. This paper presents a new method that combines text and visual information in the same latent representation space in which images and text are jointly represented. We also investigate how to select the most representative elements of the collection to build an image collection summary. The proposed method was applied to a collection of histological images and the results where evaluated both qualitatively and quantitatively by an expert. The initial results show that the proposed method is able to build a meaningful summary that can be integrated in an image collection exploration system.

关键词： visualization biomedical imaging Semantics Matrix decomposition Kidney Image retrieval Information retrieval

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Content Based Image Retrieval Using Fuzzy Relaxation and Rotational Invariance for Medical Databases

Content Based Image Retrieval Using Fuzzy Relaxation and Rot...

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International conference on Process Automation, Control and computing (PACC)

作者： C. Ramesh Babu Durai V. Duraisamy K.S.N. Sahasranaman Hindustan College of Engineering and Technology Coimbatore India Dhanalakshmi College of Engineering Chennai India

Newer generations of diagnostic machines are based on digital technologies for data acquisition and consequently with the emergence of digital archiving systems for preservation of diagnosis is rapidly increasing. The goals of Content-Based Image Retrieval (CBIR) systems is to process on collections of images, extract features and based on visual queries, extract relevant image from a repository. The fuzzy relaxation pattern matching technique using rotational invariance has been developed in the framework of fuzzy set and possibility theory. Our method takes into account the uncertainty arising in the calculated values which have to be compared for content based image retrieval. This paper looks into the basic principles and extends to the fuzzy relaxation technique for a given tolerance. Our method was extensively tested in a medical database to identify the class in the classification problem.

关键词： Image retrieval Correlation Pixel biomedical imaging visualization Wavelet transforms

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Droid Jacket: Using an Android based smartphone for team monitoring

Droid Jacket: Using an Android based smartphone for team mon...

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International Wireless Communications and Mobile computing conference, IWCMC

作者： Márcio F.M. Colunas José M. Amaral Fernandes Ilídio C. Oliveira João P. Silva Cunha Institute of Electronics Engineering and Telematics (IEETA) Department of Electronics Telecommunications and Informatics University of Aveiro Aveiro Portugal

Professionals such as First Responders are frequently exposed to extreme environmental conditions, which induce stress and fatigue during extensive periods of time. In this scenario, the main issues are the quantification and evaluation of stress and fatigue, since uncontrolled levels have a profound and negative impact on human health and performance. Based on an existing wearable monitoring solution - the Vital Jacket ® - we propose an individual and team monitoring mobile solution called DroidJacket. DroidJacket is based on Android mobile devices and provides data aggregation, processing, visualization and optionally relaying services. The DroidJacket design is plugin oriented, integrating analysis modules, namely an online ECG plugin for both real time pulse and arrhythmia detection.

关键词： Monitoring biomedical monitoring Electrocardiography Humanoid robots Mobile handsets Stress Androids

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A Cloud-Deployed 3D Medical Imaging System with Dynamically Optimized Scalability and Cloud Costs

A Cloud-Deployed 3D Medical Imaging System with Dynamically ...

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Euromicro conference on Software Engineering and Advanced Applications (SEAA)

作者： Karlheinz Dorn Vladyslav Ukis Thomas Friese Healthcare Sector Imaging and Therapy Division Siemens AG Erlangen Germany

Medical imaging is established as a foundation for the delivery of high quality patient care in medicine. The growing data volume produced per examination increases the demand for 3D visualization of such data sets in radiology. Current medical imaging systems deliver 3D functionality either through Workstations or in Client/Server solutions. Workstation deployments suffer from the requirement to transfer huge data sets to every workstation where the data is needed. Client/Server solutions often suffer from scalability limits as data from all radiologists is rendered by a single server or a server farm, adding complexity and cost. In this paper, we present a novel 3D rendering approach using Cloud computing that optimizes scalability and operational cost by architecture while flexibly adjusting to environments with low network quality.

关键词： Three dimensional displays Rendering (computer graphics) Cloud computing Servers biomedical imaging Scalability Hospitals

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Automatic segmentation of pulmonary arterial tree in computer tomography images: Segmentación automática del árbol arterial pulmonar en imágenes TAC

Automatic segmentation of pulmonary arterial tree in compute...

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Colombian conference on computing (CCC)

作者： F A. Gutiérrez D C. Ortega M. Orkisz L F. Uriza M. Hernández Hoyos Department of Psychology University of Fribourg Switzerland

Arterial tree segmentation is a major step for pulmonary embolism analysis and detection. The present document proposes a technique applied to CT images already diagnosed as embolism positive. In order to perform the segmentation of the arterial tree, the lung's region is transformed into a mask, so that the processed volume gets reduced. Then, through thresholding, region growing, and morphological operations the arterial tree is segmented in 3D. The proposed technique was evaluated by means of arterial counting in each segmented slice as well as in the original ones. That technique got a 93.72% of arterial matching on six datasets of CT images.

关键词： Image segmentation biomedical imaging Computed tomography Silicon compounds USA Councils Three dimensional displays visualization

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Segmentation of brain MRI with statistical and 2D wavelet features by using neural networks

Segmentation of brain MRI with statistical and 2D wavelet fe...

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Trendz in Information Sciences & computing (TISC)

作者： S. Javeed Hussain A. Satya Savithri P.V. Sree Devi Department of ECE BCETFW Kadapa Andhra Pradesh India Department of ECE JNTU Hyderabad Andhra Pradesh India Department of ECE Andhra University Vishakapatnam Andhra Pradesh India

In this paper, an efficient technique is proposed for the precise segmentation of normal and pathological tissues in the MRI brain images. The proposed segmentation technique initially performs classification process by utilizing FFBNN. Dual FFBNN networks are used in the classification process. The inputs for these networks are the features that are extracted in two ways from the MRI brain images. Five features are extracted from the MRI images: they are two dynamic statistical features and three 2D wavelet decomposition features. In Segmentation, the normal tissues such as WM (White Matter), GM (Gray Matter) and CSF (Cerebrospinal Fluid) are segmented from the normal MRI images and pathological tissues such as Edema and Tumor are segmented from the abnormal images. The non-cortical tissues in the normal images are removed by the preprocessing stage. The implementation result shows the efficiency of proposed tissue segmentation technique in segmenting the tissues accurately from the MRI images. The performance of the segmentation technique is evaluated by performance measures such as accuracy, specificity and sensitivity. The performance of segmentation process is analyzed using a defined set of MRI brain.

关键词： Image segmentation Magnetic resonance imaging Artificial neural networks biomedical imaging Training Asia visualization

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Human visual augmentation using wearable glasses with multiple cameras and information fusion of human eye tracking and scene understanding

Human visual augmentation using wearable glasses with multip...

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ACM/IEEE International conference on Human-Robot Interaction (HRI)

作者： Seung-Ho Yang Hyun-Woo Kim Min Young Kim IT College Kyungpook National University Daegu Korea

A smart wearable robot glasses system is proposed to assist human visual augmentation in daily life, providing a refined visual recognition result to users from multiple input images of the proposed system. It consists of a glasses-type wearable device with a front-view camera, eye-view camera, mounted display, earphone, and computing unit for signal processing. The scene-understanding process on the input image from the front-view camera can be computationally accelerated with the support of the eye-view camera that monitors the eye position of the user. For efficient information processing, the eye view camera catches the user's visual intention and attention in a given situation. It is correlated to the eye viewing direction estimated from the eye-position monitoring results of eye-view camera. The proposed device can be used to augment the human visual capability in various daily life applications.

关键词： Humans Cameras Face recognition visualization Face biomedical monitoring Robots

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A framework for semantic analysis of histopathological images using nonnegative matrix factorization

A framework for semantic analysis of histopathological image...

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Colombian conference on computing (CCC)

作者： Angel Cruz-Roa Gloria Díaz Fabio González Universidad Nacional de Colombia Bogota CO Bioingenium Research Group Universidad Central de Colombia Bioingenium Research Group Departamento de Ingeniería de Sistemas e Industrial at Univer-sidad Nacional de Colombia

This paper presents a novel and general framework for histopathology image analysis using nonnegative matrix factorization. The proposed method uses a collection-based image representation called Bag of Features (BOF) to represents the visual information of a histopathology image collection. Convex Nonnegative Matrix Factorization (CNMF) is applied to a training set of images to find a compact representation in a latent topic space. The latent representation has two important characteristics: first, CNMF is able to find representative clusters of images in the collection, second, clusters are represented by convex linear combinations of images in the training set. This latent representation is exploited in different ways by the proposed framework: concept labels can be assigned to clusters using the labels of the constituting images, representative images and visual words can be identified for each cluster, and new unlabeled images can be labeled by mapping them to the latent space. The proposed annotation model has an interesting property, it is easily interpretable since it is possible to trace those visual words present in the image which contribute the most to a given annotation. This implies that annotations in an image may be explained by identifying the regions that contributed to them. An exploratory experimentation was performed in a histopathology dataset used to diagnose a type of skin cancer called basal cell carcinoma. The preliminary results show that the combination of BOF and NMF is an interesting alternative for biomedical image collection analysis with a high level of interpretability.

关键词： visualization Semantics Training Biology Matrix decomposition Discrete cosine transforms biomedical imaging

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Efficient colon wall flattening by improved conformal mapping methodologies for computed tomography colonography

Efficient colon wall flattening by improved conformal mappin...

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IEEE Symposium on Nuclear Science (NSS/MIC)

作者： Rui Shi Hongbin Zhu David Xianfeng Gu Jerome Zhengrong Liang Department of Computer Science Stony Brook University Stony Brook NY USA Department of Radiology Stony Brook University Stony Brook NY USA Departments of Radiology Computer Science and Biomedical Engineering Stony Brook University Stony Brook NY USA

Conformal mapping provides a unique way to flatten the three-dimensional (3D) colon wall. Visualizing the flattened colon wall supplies an alternative means for the task of detecting abnormality as compared to the conventional endoscopic views. In addition to the visualization, the flattened colon wall carries supplementary geometry and texture information for computer aided detection of abnormality. It is hypothesized that utilizing both the original and the flattened 3D colon walls shall improve the detection capacity of currently available computed tomography colonography. Two major challenges exist for the conformal mapping: (1) accuracy in preserving the essential geometry and (2) efficiency in computing the mapping. This paper describes an improved conformal mapping algorithm over our previous work to accelerate the computing speed and increase the calculation accuracy. Starting from a segmented colon wall, a centerline-based search strategy is applied to remove outliers or topological noise on the segmented colon wall. The de-noised wall is then flattened by the improved conformal mapping algorithm. The algorithm was tested by patient datasets with comparison to our previous algorithm. By a PC platform of 3.0GHz CPU and 8.0 GB ROM memory, the speed was accelerated from more than 70 minutes to less than 5 minutes. In addition to the gain in speed, improvement in accuracy is observed. The gained speed and accuracy are crucially important because of the current challenges in detecting small polyps in the desired high sensitivity and efficiency for screening purpose.

关键词： Shape Geometry Read only memory

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