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BioHIPI: Biomedical Hadoop image processing Interface 3rd

3rd international conference on Machine Learning, Optimization, and Data Science (MOD)

作者： Calimeri, Francesco Caracciolo, Mirco Marzullo, Aldo Stamile, Claudio Univ Calabria Dept Math & Comp Sci Arcavacata Di Rende Italy Katholieke Univ Leuven Dept Elect Engn ESAT STADIUS Leuven Belgium

ISBN: (纸本)9783319729268;9783319729251

Nowadays, the importance of collecting large amounts of data is becoming increasingly crucial, along with the application of efficient and effective analysis techniques, in many areas. One of the most important field in which Big Data is becoming of fundamental importance is the biomedical domain, also due to the decreasing cost of acquiring and analyzing biomedical data. Furthermore, the emergence of more accessible technologies and the increasing speed-up of algorithms, also thanks to parallelization techniques, is helping at making the application of Big Data in healthcare a fast-growing field. This paper presents a novel framework, Biomedical Hadoop image processing Interface (BioHIPI), capable of storing biomedical image collections in a Distributed File System (DFS) for exploiting the parallel processing of Big Data on a cluster of machines. The work is based on the Apache Hadoop technology and makes use of the Hadoop Distributed File System (HDFS) for storing images, the MapReduce libraries for parallel programming for processing, and Yet Another Resource Negotiator (YARN) to run processes on the cluster.

关键词： Big Data Hadoop image processing

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A Novel Method for the Conversion of Scanned Electrocardiogram (ECG) image to Digital Signal 3rd

A Novel Method for the Conversion of Scanned Electrocardiogr...

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3rd international conference on Intelligent Computing and Applications (ICICA)

作者： Lewis, Macline Crecsilla Maiya, Manjunatha Sampathila, Niranjana Manipal Univ Manipal Inst Technol Dept Biomed Engn Manipal India Philips India Pvt Ltd BOP Manipal India

ISBN: (纸本)9789811055201;9789811055195

Electrocardiogram (ECG) is the record of origin and propagation of electrical potential through cardiac muscles. It provides information about heart functioning. Generally, ECG is printed on thermal paper. The person having heart abnormalities will have to maintain all the records for the diagnosis purpose, which requires large storage space and is minimized by storing in the computer using scanner. The stored data is processed manually, which is time consuming. So an automatic algorithm that is developed does the conversion of the ECG image to digital signal. In order to convert the image, image processing methods like binarization, morphological techniques have been used. Usage of morphological skeletonization helps in converting the image to digital signal form by finding the skeleton of the ECG signal. The performance of the conversion algorithm is analyzed using root-mean-square error (RMSE), and it was found good. The average error found between the binarized image and the skeletonized image is nearly 7.5%.

关键词： Electrocardiogram Binarization Morphology Skeletonization RMSE

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image annotation algorithm based on semantic similarity and multi-features 1

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3rd international conference on Smart Computing and Communications, SmartCom 2018

作者： Ni, Jingxiu Wang, Dongxing Zhang, Guoying Sun, Yanchao Xu, Xinkai Beijing Union University Beijing100101 China School of Mechanical Electronic and Information Engineering China University of Mining and Technology Beijing100083 China

ISBN: (数字)9783030057558

ISBN: (纸本)9783030057541

The paper proposed an image annotation algorithm based on semantic similarity and multi-feature fusion. The annotation algorithm draws lessons from the method of semantic extraction in natural language processing, and establishes the corresponding semantic trees for some common scenes. The scene semantic tree is constructed based on the visual features of the specific scene in the image set. Firstly, the visual features of scene images are extracted, and then the visual features are clustered by fuzzy clustering. According to the clustering results, the images are grouped, clustered at different nodes according to visual features, and the images are further grouped. After the scene semantic tree is constructed, the algorithm will extract the visual features of the image to be annotated. Furthermore, the image moves from the item node to a leaf node in the scene semantic tree according to its visual features, and the semantic keywords which appear in the route constitute the tags of the image. © 2018, Springer Nature Switzerland AG.

关键词： image annotation

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Haze removal algorithm using color attenuation prior and guided filter 18

Haze removal algorithm using color attenuation prior and gui...

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3rd international conference on Multimedia Systems and Signal processing, ICMSSP 2018

作者： Yu, Jimin Wang, Yaoheng Zhou, Shangbo College of Automation Chongqing university of Posts and Telecommunications Chongqing China College of Computer Chongqing university Chongqing China

ISBN: (纸本)9781450364577

In this paper, we describe the formatting guidelines for ACM SIG Proceedings. In this paper, we mainly introduce the haze removal algorithm which using color attenuation prior. We also propose a novel solution in the case of particular situations. Moreover, in order to make the algorithm more accurate, we propose a hierarchical searching method based on the quad-tree subdivision for estimating atmospheric light. In addition, we employ the shiftable window scheme to improve the guided filter, so that it can refine the depth map while effectively protecting image edge. Experimental result shows that our proposed method not only can obviously remove the haze from the haze image, but also the performance is more reliable in the case of particular situations.

关键词： Color

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A cable-driven parallel manipulator with force sensing capabilities for high-accuracy tissue endomicroscopy

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international JOURNAL OF computer ASSISTED RADIOLOGY AND SURGERY 2018年第5期13卷 659-669页

作者： Miyashita, Kiyoteru Vrielink, Timo Oude Mylonas, George Imperial Coll London Dept Surg & Canc HARMS Lab 3rd Floor Paterson Wing20 South Wharf Rd London W2 1PF England

Purpose Endomicroscopy (EM) provides high resolution, non-invasive histological tissue information and can be used for scanning of large areas of tissue to assess cancerous and pre-cancerous lesions and their margins. However, current robotic solutions do not provide the accuracy and force sensitivity required to perform safe and accurate tissue scanning. Methods A new surgical instrument has been developed that uses a cable-driven parallel mechanism (CPDM) to manipulate an EM probe. End-effector forces are determined by measuring the tensions in each cable. As a result, the instrument allows to accurately apply a contact force on a tissue, while at the same time offering high resolution and highly repeatable probe movement. Results 0.2 and 0.6 N force sensitivities were found for 1 and 2 DoF image acquisition methods, respectively. A back-stepping technique can be used when a higher force sensitivity is required for the acquisition of high quality tissue images. This method was successful in acquiring images on ex vivo liver tissue. Conclusion The proposed approach offers high force sensitivity and precise control, which is essential for robotic EM. The technical benefits of the current system can also be used for other surgical robotic applications, including safe autonomous control, haptic feedback and palpation.

关键词： Force sensing Endomicroscopy Cable-driven parallel mechanisms Autonomous scanning

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An algorithm for extracting centerline of the Aorta from CT/MR 3D images 18

An algorithm for extracting centerline of the Aorta from CT/...

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3rd international conference on Biomedical Signal and image processing, ICBIP 2018

作者： Ur Rahman, Sami Ur Rahman, Amin Alam, Fakhre Department of Computer Science University of Malakand Pakistan

ISBN: (纸本)9781450364362

Aorta is the main artery in the human body, originating from the left ventricle of the heart and extending down to the abdomen. The aorta distributes oxygenated blood to all parts of the body. The aorta branches off into two main arteries called coronary arteries. For investigating the heart related diseases, it is very important to know the exact geometry of the aorta and coronary arteries. One of the important parameters is to compute the centerline or skeleton of the aorta. Skeletonization is a process in which foreground image data is reduced to a single line that preserves the extent and connectivity of the original object region. From the skeleton, then different geometric parameters like the diameter of the aorta, branching angles and branching locations of the coronary arteries can be computed. The challenge in geometry computation is faced when the input image data is noisy. In this paper, we propose a new method for computing the centerline of the aorta using 3D Computed Tomography or Magnetic Resonance images. The experimental results show that the suggested algorithm performs well on image data even if the data is noisy. © 2018 Association for Computing Machinery.

关键词： Heart

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A novel approach for mammogram classification 3

A novel approach for mammogram classification

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3rd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018

作者： Nagthane, Deepika Rajurkar, Archana Computer Science and Engineering Research Scholar at MGM's College of Engineering Nanded India Computer Science and Engieering MGM's College of Engineering Nanded India

ISBN: (纸本)9781538624401

One of main reason for increase in mortality rate of woman is breast cancer. Accurate early detection of abnormalities in breast tissues seems to be the only solution for diagnosis. These detected abnormalities need to be classified for further investigation. In breast cancer research various classification techniques have been proposed to reduce the diagnostic test false positives because of the subtle appearance of the breast cancer tissues. Accurate early classification of mammogram is essential to reduce diagnostic test false positives. Hence, an attempt is made to presents an automated classification technique for mammogram. This work is divided into four steps: Pre-processing, Feature Extraction, Feature Selection and classification. In this approach cropping and resizing is used as a preprocessing technique. In next step Texture, wavelet and PCA features are extracted form mammogram, cuckoo search algorithm is enhanced to select optimal feature split points. Finally, classification is achieved using association rule agreement-based classifier model. It classifies mammogram as normal or cancerous using association rules generated from selected features. The experiments are carried out on Mammographic image Analysis Society (MIAS) database and performance of proposed method is validated over existing work using accuracy, sensitivity and specificity measures. The proposed technique has achieved accuracy 0.8289, sensitivity 0.9333 and specificity 0.7273. Results indicate the usefulness of proposed method in classification task. © 2018 IEEE.

关键词： Association rules

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Scalable high resolution panorama composition on data wall system 3

Scalable high resolution panorama composition on data wall s...

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3rd international conference on Communication, Information and Computing Technology, ICCICT 2018

作者： Shete, Pritam Prakash Sarode, Dinesh Madhukar Bose, Surojit Kumar Computer Division Bhabha Atomic Research Centre Mumbai400086 India

ISBN: (纸本)9781538620519

image stitching algorithms construct a single composite high resolution image with a larger field of view using multiple low resolution images. Data wall systems combine the power of multiple graphics cards to provide large number of pixels. In this research work, we propose and implement scalable high resolution panorama composition on the data wall system using distributed rendering. We make use of a cross platform OpenGL library for real-time panorama composition. Our algorithm works for image sources with fixed relative positions. Initially, we employ an OpenCV image processing library for panorama calibration. Subsequently, these calibration results are utilized to generate a seamless panoramic image. We construct a high resolution 3×3 data wall system using commodity projectors. We achieve a seamless display with the help of geometric alignment of projector regions and edge blending in overlapping regions. Conventional display devices with their limited image resolution lose details provided by high resolution panorama because of data compression. We integrate panorama composition and the data wall system using distributed rendering. We distribute panorama composition to rendering workstations, which compute their respective screen space bounding regions and operate within it. It provides high resolution panorama with greater details on the data wall system. © 2018 IEEE.

关键词： Calibration

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6D Pose Estimation Using an Improved Method Based on Point Pair Features

6D Pose Estimation Using an Improved Method Based on Point P...

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4th international conference on Control, Automation and Robotics (ICCAR)

作者： Vidal, Joel Lin, Chyi-Yeu Marti, Robert Natl Taiwan Univ Sci & Technol Dept Mech Engn Taipei Taiwan Univ Girona Comp Vis & Robot Grp Girona Spain

ISBN: (纸本)9781538663387

The Point Pair Feature [4] has been one of the most successful 6D pose estimation method among model-based approaches as an efficient, integrated and compromise alternative to the traditional local and global pipelines. During the last years, several variations of the algorithm have been proposed. Among these extensions, the solution introduced by Hinterstoisser et al. [6] is a major contribution. This work presents a variation of this PPF method applied to the SIXD Challenge datasets presented at the 3rd international Workshop on Recovering 6D Object Pose held at the ICCV 2017. We report an average recall of 0.77 for all datasets and overall recall of 0.82, 0.67, 0.85, 0.37, 0.97 and 0.96 for hinterstoisser, tless, tudlight, rutgers, tejani and doumanoglou datasets, respectively.

关键词： 6D pose estimation 3D object recognition object detection 3D computer vision robotics range image

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IOT in HealthCare: Smart emotion detector utilizing wearable bio sensors 3

IOT in HealthCare: Smart emotion detector utilizing wearable...

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3rd IEEE international conference on Recent Trends in Electronics, Information and Communication Technology, RTEICT 2018

作者： Patil, Manish N. Surve, Anil R. Walchand College of Engineering Department of Computer Science and Engineering Sangli Maharashtra416415 India

ISBN: (纸本)9781538624401

Nowday's healthcare is crucial part in the society. Almost every single person is struggling with health related problems. By using previous research and survey we found that every disease is indirectly connected/related with the patient's emotional state or we can say mental health. So as per the literature survey user's emotions are performing the biggest role in his/her health. In today's world of technology where computers are utilized to recognizing human emotion states, but problem is that there are too many technologies are available for emotion detection such as image processing but they have few demerits, due to that it is difficult to recognize real emotion from the fake emotions. by seeing the growth of technological world this domain needs more attention and contribution of research. This paper proposes a system to make existing emotion detection more efficient. Bio sensors (Non Invasive) are used to collect emotion related data from human body. By utilizing EDA (Electro Dermal Activity) we measure skin conductance of human body to recognize the various stimuli. After the emotion detection using behavioural analysis (Emotion Pattern) we can predict the future possible diseases. © 2018 IEEE.

关键词： Ubiquitous computing

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