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computer aided diagnosis

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https://www.readbyqxmd.com/read/28227002/3d-limb-movement-tracking-and-analysis-for-neurological-dysfunctions-of-neonates-using-multi-camera-videos
#1
Irene Yu-Hua Gu, Grzegorz Sowulewski, Yixiao Yun, Anders Flisberg, Magnus Thordstein, Irene Yu-Hua Gu, Grzegorz Sowulewski, Yixiao Yun, Anders Flisberg, Magnus Thordstein, Irene Yu-Hua Gu, Grzegorz Sowulewski, Anders Flisberg, Yixiao Yun, Magnus Thordstein
Central nervous system dysfunction in infants may be manifested through inconsistent, rigid and abnormal limb movements. Detection of limb movement anomalies associated with such neurological dysfunctions in infants is the first step towards early treatment for improving infant development. This paper addresses the issue of detecting and quantifying limb movement anomalies in infants through non-invasive 3D image analysis methods using videos from multiple camera views. We propose a novel scheme for tracking 3D time trajectories of markers on infant's limbs by video analysis techniques...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226976/thorax-disease-diagnosis-using-deep-convolutional-neural-network
#2
Jie Chen, Xianbiao Qi, Osmo Tervonen, Olli Silven, Guoying Zhao, Matti Pietikainen, Jie Chen, Xianbiao Qi, Osmo Tervonen, Olli Silven, Guoying Zhao, Matti Pietikainen, Osmo Tervonen, Xianbiao Qi, Jie Chen, Matti Pietikainen, Olli Silven, Guoying Zhao
Computer aided diagnosis (CAD) is an important issue, which can significantly improve the efficiency of doctors. In this paper, we propose a deep convolutional neural network (CNN) based method for thorax disease diagnosis. We firstly align the images by matching the interest points between the images, and then enlarge the dataset by using Gaussian scale space theory. After that we use the enlarged dataset to train a deep CNN model and apply the obtained model for the diagnosis of new test data. Our experimental results show our method achieves very promising results...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226760/a-new-approach-of-oral-cancer-detection-using-bilateral-texture-features-in-digital-infrared-thermal-images
#3
M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, M Chakraborty, S Mukhopadhyay, A Dasgupta, S Patsa, N Anjum, J G Ray, S Patsa, A Dasgupta, N Anjum, M Chakraborty, S Mukhopadhyay, J G Ray
Oral cancer is one of the most prevalent form of cancer and its severity is aggrandized specially among the socio-economically backward population in developing countries. A major fraction of patient population is unable to avail diagnosis for oral cancer due to scarcity of state-of-the-art infrastructure and experienced oral and maxillofacial pathologist. Contemporary gold standard of oral cancer confirmation relies on biopsy report. But biopsy is invasive and thus patients are usually reluctant to undergo this test...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226755/automatic-detection-of-melanoma-using-broad-extraction-of-features-from-digital-images
#4
M H Jafari, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, M H Jafari, S Samavi, N Karimi, S M R Soroushmehr, K Ward, K Najarian, K Ward, M H Jafari, S M R Soroushmehr, S Samavi, K Najarian, N Karimi
Automatic and reliable diagnosis of skin cancer, as a smartphone application, is of great interest. Among different types of skin cancers, melanoma is the most dangerous one which causes most deaths. Meanwhile, melanoma is curable if it were diagnosed in its early stages. In this paper we propose an efficient system for prescreening of pigmented skin lesions for malignancy using general-purpose digital cameras. These images can be captured by a smartphone or a digital camera. This could be beneficial in different applications, such as computer aided diagnosis and telemedicine applications...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226751/deep-neural-ensemble-for-retinal-vessel-segmentation-in-fundus-images-towards-achieving-label-free-angiography
#5
A Lahiri, Abhijit Guha Roy, Debdoot Sheet, Prabir Kumar Biswas, A Lahiri, Abhijit Guha Roy, Debdoot Sheet, Prabir Kumar Biswas, Debdoot Sheet, Prabir Kumar Biswas, A Lahiri
Automated segmentation of retinal blood vessels in label-free fundus images entails a pivotal role in computed aided diagnosis of ophthalmic pathologies, viz., diabetic retinopathy, hypertensive disorders and cardiovascular diseases. The challenge remains active in medical image analysis research due to varied distribution of blood vessels, which manifest variations in their dimensions of physical appearance against a noisy background. In this paper we formulate the segmentation challenge as a classification task...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226579/a-deep-convolutional-neural-network-for-bleeding-detection-in-wireless-capsule-endoscopy-images
#6
Xiao Jia, Max Q-H Meng, Xiao Jia, Max Q-H Meng, Xiao Jia, Max Q-H Meng
Wireless Capsule Endoscopy (WCE) is a standard non-invasive modality for small bowel examination. Recently, the development of computer-aided diagnosis (CAD) systems for gastrointestinal (GI) bleeding detection in WCE image videos has become an active research area with the goal of relieving the workload of physicians. Existing methods based primarily on handcrafted features usually give insufficient accuracy for bleeding detection, due to their limited capability of feature representation. In this paper, we present a new automatic bleeding detection strategy based on a deep convolutional neural network and evaluate our method on an expanded dataset of 10,000 WCE images...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226577/semi-advised-learning-model-for-skin-cancer-diagnosis-based-on-histopathalogical-images
#7
Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily, Ammara Masood, Adel Al-Jumaily
Computer aided classification of skin cancer images is an active area of research and different classification methods has been proposed so far. However, the supervised classification models based on insufficient labeled training data can badly influence the diagnosis process. To deal with the problem of limited labeled data availability this paper presents a semi advised learning model for automated recognition of skin cancer using histopathalogical images. Deep belief architecture is constructed using unlabeled data by making efficient use of limited labeled data for fine tuning done the classification model...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226447/automatic-tissue-characterization-of-air-trapping-in-chest-radiographs-using-deep-neural-networks
#8
Awais Mansoor, Geovanny Perez, Gustavo Nino, Marius George Linguraru, Awais Mansoor, Geovanny Perez, Gustavo Nino, Marius George Linguraru, Geovanny Perez, Marius George Linguraru, Gustavo Nino, Awais Mansoor
Significant progress has been made in recent years for computer-aided diagnosis of abnormal pulmonary textures from computed tomography (CT) images. Similar initiatives in chest radiographs (CXR), the common modality for pulmonary diagnosis, are much less developed. CXR are fast, cost effective and low-radiation solution to diagnosis over CT. However, the subtlety of textures in CXR makes them hard to discern even by trained eye. We explore the performance of deep learning abnormal tissue characterization from CXR...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28219805/fusion-of-spatial-gray-level-dependency-and-fractal-texture-features-for-the-characterization-of-thyroid-lesions
#9
U Raghavendra, U Rajendra Acharya, Anjan Gudigar, Jen Hong Tan, Hamido Fujita, Yuki Hagiwara, Filippo Molinari, Pailin Kongmebhol, Kwan Hoong Ng
Thyroid is a small gland situated at the anterior side of the neck and one of the largest glands of the endocrine system. The abrupt cell growth or malignancy in the thyroid gland may cause thyroid cancer. Ultrasound images distinctly represent benign and malignant lesions, but accuracy may be poor due to subjective interpretation. Computer Aided Diagnosis (CAD) can minimize the errors created due to subjective interpretation and assists to make fast accurate diagnosis. In this work, fusion of Spatial Gray Level Dependence Features (SGLDF) and fractal textures are used to decipher the intrinsic structure of benign and malignant thyroid lesions...
February 6, 2017: Ultrasonics
https://www.readbyqxmd.com/read/28215064/cardiac-computational-modeling-of-ventricular-tachycardia-and-cardiac-resynchronization-therapy-a-clinical-perspective
#10
Zhong Chen, Steve Niederer, Nesan Shanmugam, Maxime Sermesant, Christopher A Rinaldi
Computational modeling has contributed to the understanding of the normal cardiac electrophysiology and the mechanisms underlying arrhythmogenesis and arrhythmia maintenance. Our improved understanding of cardiac physiology and access to faster computational power have allowed us to integrate many layers of biological systems, gain further insight into the mechanism of cardiac pathology and moved from small scale molecular and cellular models to integrated 3-dimensional models representing the anatomy, electrophysiology and hemodynamic parameters on a organ scale...
February 17, 2017: Minerva Cardioangiologica
https://www.readbyqxmd.com/read/28214460/managing-acetabular-defects-in-total-hip-arthroplasty
#11
Brian Park, Frank Liporace, Scott Marwin
With the aging population and rising incidence of primary total joint arthroplasty has come the increasing incidence of revision total hip arthroplasties. One challenge in revision total hip arthroplasty is dealing with acetabular defects. The orthopaedic surgeon who chooses to take on these challenges requires a proper method for the evaluation of these defects as well as an evidence-based treatment algorithm. Initial assessment requires appropriate use and interpretation of imaging modalities such as x-rays and computed tomography...
January 2017: Bulletin of the Hospital for Joint Diseases
https://www.readbyqxmd.com/read/28211015/fifty-years-of-computer-analysis-in-chest-imaging-rule-based-machine-learning-deep-learning
#12
REVIEW
Bram van Ginneken
Half a century ago, the term "computer-aided diagnosis" (CAD) was introduced in the scientific literature. Pulmonary imaging, with chest radiography and computed tomography, has always been one of the focus areas in this field. In this study, I describe how machine learning became the dominant technology for tackling CAD in the lungs, generally producing better results than do classical rule-based approaches, and how the field is now rapidly changing: in the last few years, we have seen how even better results can be obtained with deep learning...
February 16, 2017: Radiological Physics and Technology
https://www.readbyqxmd.com/read/28194685/selective-search-and-intensity-context-based-retina-vessel-image-segmentation
#13
Zhaohui Tang, Jin Zhang, Weihua Gui
In the framework of computer-aided diagnosis of eye disease, a new contextual image feature named influence degree of average intensity is proposed for retinal vessel image segmentation. This new feature evaluates the influence degree of current detected pixel decreasing the average intensity of the local row where that pixel located. Firstly, Hessian matrix is introduced to detect candidate regions, for the reason of accelerating segmentation. Then, the influence degree of average intensity of each pixel is extracted...
March 2017: Journal of Medical Systems
https://www.readbyqxmd.com/read/28187893/computer-aided-grading-of-gliomas-based-on-local-and-global-mri-features
#14
Kevin Li-Chun Hsieh, Chung-Ming Lo, Chih-Jou Hsiao
BACKGROUND AND OBJECTIVES: A computer-aided diagnosis (CAD) system based on quantitative magnetic resonance imaging (MRI) features was developed to evaluate the malignancy of diffuse gliomas, which are central nervous system tumors. METHODS: The acquired image database for the CAD performance evaluation was composed of 34 glioblastomas and 73 diffuse lower-grade gliomas. In each case, tissues enclosed in a delineated tumor area were analyzed according to their gray-scale intensities on MRI scans...
February 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28187889/gift-cloud-a-data-sharing-and-collaboration-platform-for-medical-imaging-research
#15
Tom Doel, Dzhoshkun I Shakir, Rosalind Pratt, Michael Aertsen, James Moggridge, Erwin Bellon, Anna L David, Jan Deprest, Tom Vercauteren, S├ębastien Ourselin
OBJECTIVES: Clinical imaging data are essential for developing research software for computer-aided diagnosis, treatment planning and image-guided surgery, yet existing systems are poorly suited for data sharing between healthcare and academia: research systems rarely provide an integrated approach for data exchange with clinicians; hospital systems are focused towards clinical patient care with limited access for external researchers; and safe haven environments are not well suited to algorithm development...
February 2017: Computer Methods and Programs in Biomedicine
https://www.readbyqxmd.com/read/28185926/using-a-genetic-fuzzy-algorithm-as-a-computer-aided-diagnosis-tool-on-saudi-arabian-breast-cancer-database
#16
Abir Alharbi, F Tchier
The computer-aided diagnosis has become one of the major research topics in medical diagnostics. In this research paper, we focus on designing an automated computer diagnosis by combining two major methodologies, namely the fuzzy base systems and the evolutionary genetic algorithms and applying them to the Saudi Arabian breast cancer diagnosis database, to be employed for assisting physicians in the early detection of breast cancers, and hence obtaining an early-computerized diagnosis complementary to that by physicians...
February 6, 2017: Mathematical Biosciences
https://www.readbyqxmd.com/read/28185635/a-review-of-lung-cancer-screening-and-the-role-of-computer-aided-detection
#17
REVIEW
B Al Mohammad, P C Brennan, C Mello-Thoms
Lung cancer is the leading cause of cancer-related death worldwide; however, early diagnosis of lung cancer leads to higher survival rates. The National Lung Screening Trial (NLST) demonstrated that scanning with low-dose computed tomography (LDCT) led to a 20% reduction in mortality rate in a high-risk population. This paper covers new developments in screening eligibility criteria and the possible benefits and the harm of screening with CT. To make the screening process more feasible and help reduce the rate of missed lung nodules, computer-aided detection (CAD) has been introduced to assist radiologists in lung nodule detection...
February 6, 2017: Clinical Radiology
https://www.readbyqxmd.com/read/28185616/tuberculous-peritonitis
#18
Urvashi Vaid, Gregory C Kane
Tuberculous peritonitis is rare in the United States but continues to be reported to occur in certain high-risk populations, which include patients with AIDS or cirrhosis, patients on continuous ambulatory peritoneal dialysis, recent immigrants from areas of high endemicity, and those who are immunosuppressed. The diagnosis of this disease requires a high clinical index of suspicion and should be considered in the differential of ascites with a lymphocyte predominance and serum-ascitic albumin gradient of <1...
January 2017: Microbiology Spectrum
https://www.readbyqxmd.com/read/28168681/normal-model-construction-for-statistical-image-analysis-of-torso-fdg-pet-images-based-on-anatomical-standardization-by-ct-images-from-fdg-pet-ct-devices
#19
Kenshiro Takeda, Takeshi Hara, Xiangrong Zhou, Tetsuro Katafuchi, Masaya Kato, Satoshi Ito, Keiichi Ishihara, Shinichiro Kumita, Hiroshi Fujita
PURPOSE: A better understanding of the standardized uptake value (SUV) ranges of fludeoxyglucose positron emission tomography (FDG-PET) is crucial for radiologists. We have developed a statistical image analysis method for FDG-PET imaging of the torso, based on comparisons with normal data. The purpose of this study was to verify the accuracy of the normal model and usefulness of the statistical image analysis method by using typical cancer cases in the liver, lungs, and abdomen. METHODS: Our study and the data collection (49 normal and 34 abnormal cases, in terms of PET/CT findings) were approved by the institutional review board...
February 6, 2017: International Journal of Computer Assisted Radiology and Surgery
https://www.readbyqxmd.com/read/28168531/clinical-and-imaging-features-indicative-of-clinically-worrisome-pneumatosis-key-components-to-identifying-proper-medical-intervention
#20
Riya Goyal, Hwayoung K Lee, Meredith Akerman, Leonora W Mui
PURPOSE: The purpose of this retrospective study was to determine clinical and imaging factors on computed tomography (CT) associated with clinically worrisome pneumatosis intestinalis (PI) that may aid in the decision to provide conservative management or urgent surgical intervention. METHODS: Informed consent was waived in this IRB approved study. Imaging features assessed included the presence, location, and pattern of PI, bowel dilatation, thickening, enhancement, stranding, portal venous (PV) and mesenteric venous gas, mesenteric edema, free air, and ascites...
February 6, 2017: Emergency Radiology
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