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https://www.readbyqxmd.com/read/28231511/automated-diagnosis-of-congestive-heart-failure-using-dual-tree-complex-wavelet-transform-and-statistical-features-extracted-from-2s-of-ecg-signals
#1
Vidya K Sudarshan, U Rajendra Acharya, Shu Lih Oh, Muhammad Adam, Jen Hong Tan, Chua Kuang Chua, Kok Poo Chua, Ru San Tan
Identification of alarming features in the electrocardiogram (ECG) signal is extremely significant for the prediction of congestive heart failure (CHF). ECG signal analysis carried out using computer-aided techniques can speed up the diagnosis process and aid in the proper management of CHF patients. Therefore, in this work, dual tree complex wavelets transform (DTCWT)-based methodology is proposed for an automated identification of ECG signals exhibiting CHF from normal. In the experiment, we have performed a DTCWT on ECG segments of 2s duration up to six levels to obtain the coefficients...
February 7, 2017: Computers in Biology and Medicine
https://www.readbyqxmd.com/read/28230717/imaging-performance-of-a-handheld-ultrasound-system-with-real-time-computer-aided-detection-of-lumbar-spine-anatomy-a-feasibility-study
#2
Mohamed Tiouririne, Adam J Dixon, F William Mauldin, David Scalzo, Arun Krishnaraj
OBJECTIVES: The aim of this study was to evaluate the imaging performance of a handheld ultrasound system and the accuracy of an automated lumbar spine computer-aided detection (CAD) algorithm in the spines of human subjects. MATERIALS AND METHODS: This study was approved by the institutional review board of the University of Virginia. The authors designed a handheld ultrasound system with enhanced bone image quality and fully automated CAD of lumbar spine anatomy...
February 22, 2017: Investigative Radiology
https://www.readbyqxmd.com/read/28230661/predicting-progression-in-barrett-s-esophagus-development-and-validation-of-the-barrett-s-esophagus-assessment-of-risk-score-bear-score
#3
Craig S Brown, Brittany Lapin, Jay L Goldstein, John G Linn, Mark S Talamonti, Joann Carbray, Michael B Ujiki
OBJECTIVE: To develop and validate a scoring tool capable of accurately predicting which patients with Barrett's esophagus (BE) will progress to dysplasia and/or esophageal adenocarcinoma. BACKGROUND: Endoscopic therapies have emerged capable of eradicating BE with high efficacy and low complication rates, but which patients should receive treatment is still debated. Current knowledge of risk factors is insufficient to allow for the accurate prediction of which patients will progress to dysplasia or adenocarcinoma...
February 22, 2017: Annals of Surgery
https://www.readbyqxmd.com/read/28229911/diagnostic-accuracy-of-carotid-intima-media-thickness-in-predicting-coronary-plaque-burden-on-coronary-computed-tomography-angiography-in-patients-with-obstructive-sleep-apnoea
#4
David J Murphy, Sophie J Crinion, Ciaran E Redmond, Gerard M Healy, Walter T McNicholas, Silke Ryan, Jonathan D Dodd
AIM: To assess the diagnostic accuracy of common carotid artery intima media thickness (CIMT) for coronary artery disease (CAD) detection in patients with obstructive sleep apnoea (OSA). MATERIALS & METHODS: Patients with clinically suspected OSA prospectively underwent polysomnography (PSG), ultrasound CIMT measurement and coronary computed tomography angiography (CTA). An average CIMT of ≥0.9 mm in either common carotid artery designated as a positive test...
February 11, 2017: Journal of Cardiovascular Computed Tomography
https://www.readbyqxmd.com/read/28229522/fused-silica-capillaries-with-two-segments-of-different-internal-diameters-and-inner-surface-roughnesses-prepared-by-etching-with-supercritical-water-and-used-for-volume-coupling-electrophoresis
#5
Marie Horká, Pavel Karásek, Michal Roth, Karel Šlais
In the present work, single-piece fused silica capillaries with two different internal diameter segments featuring different inner surface roughness were prepared by new etching technology with supercritical water and used for volume coupling electrophoresis. The concept of separation and on-line pre-concentration of analytes in high conductivity matrix is based on the on-line large-volume sample pre-concentration by the combination of transient isotachophoretic stacking and sweeping of charged proteins in micellar electrokinetic chromatography using non-ionogenic surfactant...
February 22, 2017: Electrophoresis
https://www.readbyqxmd.com/read/28227985/a-multi-criteria-evaluation-platform-for-segmentation-algorithms
#6
Pierre Laurent, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Pierre Laurent, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Thierry Cresson, Carlos Vazquez, Nicola Hagemeister, Jacques A de Guise, Pierre Laurent
The purpose of this paper is to present a platform for evaluating segmentation algorithms that detect anatomical structures in medical images. Structure detection being subject to human interpretation, we first describe a method to define a ground truth model, i.e. a generated bronze standard, that will be the reference for subsequent analysis. This bronze standard will be characterized in order to retrieve its confidence level that will later be used to normalize the algorithm evaluation. We then describe how the developed platform helps in evaluating algorithm performances described using five evaluation criteria: accuracy, reliability, robustness, under/over segmentation sensitivity and outlier sensitivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227960/automated-volumetry-for-unilateral-hippocampal-sclerosis-detection-in-patients-with-temporal-lobe-epilepsy
#7
Cristina Martins, Nadia Moreira da Silva, Guilherme Silva, Verena E Rozanski, Joao Paulo Silva Cunha, Cristina Martins, Nadia Moreira da Silva, Guilherme Silva, Verena E Rozanski, Joao Paulo Silva Cunha, Joao Paulo Silva Cunha, Guilherme Silva, Verena E Rozanski, Nadia Moreira da Silva, Cristina Martins
Hippocampal sclerosis (HS) is the most common cause of temporal lobe epilepsy (TLE) and can be identified in magnetic resonance imaging as hippocampal atrophy and subsequent volume loss. Detecting this kind of abnormalities through simple radiological assessment could be difficult, even for experienced radiologists. For that reason, hippocampal volumetry is generally used to support this kind of diagnosis. Manual volumetry is the traditional approach but it is time consuming and requires the physician to be familiar with neuroimaging software tools...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227783/tooth-separation-from-dental-model-using-segmentation-field
#8
Hao Wang, Zhongyi Li, Hao Wang, Zhongyi Li, Zhongyi Li, Hao Wang
Tooth segmentation on dental model is an essential step of computer-aided-design systems for orthodontic virtual treatment planning. However, efficiently identifying cutting boundary to separate tooth from dental model still remains a challenge, due to various geometrical shapes of teeth, complex tooth arrangements and varying degrees of crowding problem. Most segmentation approaches presented before are not able to achieve a balance between fine segmentation results and simple operating procedure. In this article, we present a novel and efficient framework that achieves tooth segmentation based on the segmentation field...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227363/3d-gabor-wavelet-based-vessel-filtering-of-photoacoustic-images
#9
Israr Ul Haq, Ryo Nagoaka, Takahiro Makino, Takuya Tabata, Yoshifumi Saijo, Israr Ul Haq, Ryo Nagoaka, Takahiro Makino, Takuya Tabata, Yoshifumi Saijo, Ryo Nagoaka, Yoshifumi Saijo, Takahiro Makino, Takuya Tabata
Filtering and segmentation of vasculature is an important issue in medical imaging. The visualization of vasculature is crucial for the early diagnosis and therapy in numerous medical applications. This paper investigates the use of Gabor wavelet to enhance the effect of vasculature while eliminating the noise due to size, sensitivity and aperture of the detector in 3D Optical Resolution Photoacoustic Microscopy (OR-PAM). A detailed multi-scale analysis of wavelet filtering and Hessian based method is analyzed for extracting vessels of different sizes since the blood vessels usually vary with in a range of radii...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227328/effect-of-importance-sampling-on-robust-segmentation-of-audio-cough-events-in-noisy-environments
#10
Jesus Monge-Alvarez, Carlos Hoyos-Barcelo, Paul Lesso, Javier Escudero, Keshav Dahal, Pablo Casaseca-de-la-Higuera, Jesus Monge-Alvarez, Carlos Hoyos-Barcelo, Paul Lesso, Javier Escudero, Keshav Dahal, Pablo Casaseca-de-la-Higuera, Javier Escudero, Jesus Monge-Alvarez, Keshav Dahal, Carlos Hoyos-Barcelo, Pablo Casaseca-De-La-Higuera, Paul Lesso
This paper proposes a new cough detection system based on audio signals acquired from conventional smartphones. The system relies on local Hu moments to characterize cough events and a Λ-NN classifier to distinguish cough events from non-cough ones (speech, laugh, sneeze, etc.) and noisy sounds. To deal with the unbalance between classes, we employ Distinct-Borderline2 Synthetic Minority Oversampling Technique and a bespoke cost matrix. The system additionally features a post-processing module to avoid isolated false negatives and, this way, increases sensitivity...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227202/snoring-sound-classification-from-respiratory-signal
#11
Mehrnaz Shokrollahi, Shumit Saha, Peyman Hadi, Frank Rudzicz, Azadeh Yadollahi, Mehrnaz Shokrollahi, Shumit Saha, Peyman Hadi, Frank Rudzicz, Azadeh Yadollahi, Frank Rudzicz, Mehrnaz Shokrollahi, Azadeh Yadollahi, Peyman Hadi, Shumit Saha
Snoring is common in the general population and the irregularity could lead to the presence of Obstructive sleep apnea. Diagnosis of OSA could therefore be made by snoring sound analysis. However, there is still a shortage of robust methods to automatically detect snoring sounds without the need to calibrate for every individual. In this paper, a novel method based on neural network is proposed to classify breathing sound episodes from snoring and non-snoring sound segments. Our snore detection algorithm was applied to the tracheal sounds of nine individuals with different OSA severities...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28227003/automated-segmentation-and-classification-of-cell-nuclei-in-immunohistochemical-breast-cancer-images-with-estrogen-receptor-marker
#12
Julio Oscanoa, Franco Doimi, Richard Dyer, Jhahaira Araujo, Joseph Pinto, Benjamin Castaneda, Julio Oscanoa, Franco Doimi, Richard Dyer, Jhahaira Araujo, Joseph Pinto, Benjamin Castaneda, Jhahaira Araujo, Franco Doimi, Julio Oscanoa, Richard Dyer, Benjamin Castaneda, Joseph Pinto
Breast cancer is the most common malignant tumor in women worldwide. In recent years, there has been an increasing use of immunohistochemistry (the process of detecting the expression of certain proteins in cytological images) to obtain useful information for diagnosis. This paper presents an efficient algorithm that automatically detects breast cancer cell nuclei and divides them into two groups: those that express the ER marker and those that do not. First, the areas that belong to the carcinoma are automatically identified...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226747/automatic-detection-of-neovascularization-on-optic-disk-region-with-feature-extraction-and-support-vector-machine
#13
Shuang Yu, Di Xiao, Yogesan Kanagasingam, Shuang Yu, Di Xiao, Yogesan Kanagasingam, Di Xiao, Yogesan Kanagasingam, Shuang Yu
Neovascularization (NV) is a definitive indicator for the onset of Proliferative Diabetic Retinopathy (PDR). The new vessels are fragile and prone to bleed, leading to high risk of sudden vision loss. Automatic detection of NV is an important task in automatic Diabetic Retinopathy (DR) screening as a consequence of the unmet requirement between the growing number of DR patients and limited number of ophthalmologists. This paper focuses on the computer aided detection of neovascularization in the optic disk region...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226741/automated-detection-of-neovascularization-for-proliferative-diabetic-retinopathy-screening
#14
Sohini Roychowdhury, Dara D Koozekanani, Keshab K Parhi, Sohini Roychowdhury, Dara D Koozekanani, Keshab K Parhi, Dara D Koozekanani, Keshab K Parhi, Sohini Roychowdhury
Neovascularization is the primary manifestation of proliferative diabetic retinopathy (PDR) that can lead to acquired blindness. This paper presents a novel method that classifies neovascularizations in the 1-optic disc (OD) diameter region (NVD) and elsewhere (NVE) separately to achieve low false positive rates of neovascularization classification. First, the OD region and blood vessels are extracted. Next, the major blood vessel segments in the 1-OD diameter region are classified for NVD, and minor blood vessel segments elsewhere are classified for NVE...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226736/automatic-segmentation-of-lungs-in-spect-images-using-active-shape-model-trained-by-meshes-delineated-in-ct-images
#15
Cheimariotis Grigorios-Aris, Al-Mashat Mariam, Haris Kostas, Aletras H Anthony, Jogi Jonas, Bajc Marika, Maglaveras Nicolaos, Heiberg Einar, Cheimariotis Grigorios-Aris, Al-Mashat Mariam, Haris Kostas, Aletras H Anthony, Jogi Jonas, Bajc Marika, Maglaveras Nicolaos, Heiberg Einar, Bajc Marika, Al-Mashat Mariam, Jogi Jonas, Heiberg Einar, Haris Kostas, Maglaveras Nicolaos, Aletras H Anthony, Cheimariotis Grigorios-Aris
This paper presents a fully automated method for segmentation of 3D SPECT ventilation and perfusion images. It relies on statistical information on lung shape derived by CT manual segmentation and its main processing steps are: shape model extraction, binary segmentation, positioning of mean shape in SPECT images and iterative shape adaptation based on intensity profiles and on what is considered `plausible' lung shape. The Active Shape Model is used to generate accurate anatomic results in SPECT images with functional information and thus unclear borders, especially in the case of pathologies...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226731/automatic-detection-of-hemorrhage-and-surgical-instrument-in-laparoscopic-surgery-image
#16
Kyungmin Jo, Bareum Choi, Songe Choi, Youngjin Moon, Jaesoon Choi, Kyungmin Jo, Bareum Choi, Songe Choi, Youngjin Moon, Jaesoon Choi, Songe Choi, Jaesoon Choi, Bareum Choi, Youngjin Moon, Kyungmin Jo
In this paper, we propose a new method for detecting hemorrhage areas and surgical instruments in robot-assisted laparoscopic surgery images. The proposed scheme utilizes CIELAB information to identify a region of interest (ROI) and segment it. Histogram equalization and Otsu's method are also adopted to compute the detection threshold. Detection is performed automatically and additional adjustment of parameters is not needed. Experiments to verify the proposed algorithm were conducted using actual robot-assisted laparoscopic surgery images...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226712/segmentation-of-angiodysplasia-lesions-in-wce-images-using-a-map-approach-with-markov-random-fields
#17
Pedro M Vieira, Bruno Goncalves, Carla R Goncalves, Carlos S Lima, Pedro M Vieira, Bruno Goncalves, Carla R Goncalves, Carlos S Lima, Pedro M Vieira, Carla R Goncalves, Bruno Goncalves, Carlos S Lima
This paper deals with the segmentation of angiodysplasias in wireless capsule endoscopy images. These lesions are the cause of almost 10% of all gastrointestinal bleeding episodes, and its detection using the available software presents low sensitivity. This work proposes an automatic selection of a ROI using an image segmentation module based on the MAP approach where an accelerated version of the EM algorithm is used to iteratively estimate the model parameters. Spatial context is modeled in the prior probability density function using Markov Random Fields...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226684/simplified-computer-aided-detection-scheme-of-microcalcification-clusters-in-digital-breast-tomosynthesis-images
#18
Ji-Wook Jeong, Seung-Hoon Chae, Eun Young Chae, Hak Hee Kim, Young Wook Choi, Sooyeul Lee, Ji-Wook Jeong, Seung-Hoon Chae, Eun Young Chae, Hak Hee Kim, Young Wook Choi, Sooyeul Lee, Sooyeul Lee, Ji-Wook Jeong, Hak Hee Kim, Eun Young Chae, Young Wook Choi, Seung-Hoon Chae
A computer-aided detection (CADe) algorithm for clustered microcalcifications (MCs) in reconstructed digital breast tomosynthesis (DBT) images is suggested. The MC-like objects were enhanced by a Hessian-based 3D calcification response function, and a signal-to-noise ratio (SNR) enhanced image was also generated to screen the MC clustering seed objects. A connected component segmentation method was used to detect the cluster seed objects, which were considered as potential clustering centers of MCs. Bounding cubes for the accepted clustering seed candidate were generated and the overlapping cubes were combined and examined...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226599/identifying-glaucoma-patients-by-applying-multivariate-analyses-of-cardiovascular-signals
#19
Andreas Voss, Claudia Fischer, Cristina Gonzalez Martinez, Eva Koch, Niklas Plange, Kathleen Kunert, Andreas Voss, Claudia Fischer, Cristina Gonzalez Martinez, Eva Koch, Niklas Plange, Kathleen Kunert, Claudia Fischer, Kathleen Kunert, Niklas Plange, Cristina Gonzalez Martinez, Eva Koch, Andreas Voss
Glaucoma is a disease that damages the eye's optic nerve. However, the exact cause of this optic nerve damage is not yet fully understood. Besides the factors of age, genetics and others, such as obesity, medication and migraines, a vascular dysfunction is believed to be a significant factor leading to glaucoma. This study's objective was to investigate whether these vascular dysfunctions could be recognized by analyzing cardiovascular regulation in glaucoma patients. Linear and nonlinear methods were applied to the extracted heart rate (HR), and systolic/ diastolic blood pressure (DBP) time series to discriminate between 35 healthy controls and 20 glaucoma patients...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/28226493/towards-an-unsupervised-device-for-the-diagnosis-of-childhood-pneumonia-in-low-resource-settings-automatic-segmentation-of-respiratory-sounds
#20
J Sola, F Braun, E Muntane, C Verjus, M Bertschi, F Hugon, S Manzano, M Benissa, A Gervaix, J Sola, F Braun, E Muntane, C Verjus, M Bertschi, F Hugon, S Manzano, M Benissa, A Gervaix, F Hugon, C Verjus, A Gervaix, S Manzano, M Bertschi, E Muntane, M Benissa, J Sola, F Braun
Pneumonia remains the worldwide leading cause of children mortality under the age of five, with every year 1.4 million deaths. Unfortunately, in low resource settings, very limited diagnostic support aids are provided to point-of-care practitioners. Current UNICEF/WHO case management algorithm relies on the use of a chronometer to manually count breath rates on pediatric patients: there is thus a major need for more sophisticated tools to diagnose pneumonia that increase sensitivity and specificity of breath-rate-based algorithms...
August 2016: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
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