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Machine learning and ultrasound

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https://www.readbyqxmd.com/read/30532667/a-review-of-denoising-medical-images-using-machine-learning-approaches
#1
REVIEW
Prabhpreet Kaur, Gurvinder Singh, Parminder Kaur
Background: This paper attempts to identify suitable Machine Learning (ML) approach for image denoising of radiology based medical application. The Identification of ML approach is based on (i) Review of ML approach for denoising (ii) Review of suitable Medical Denoising approach. Discussion: The review focuses on six application of radiology: Medical Ultrasound (US) for fetus development, US Computer Aided Diagnosis (CAD) and detection for breast, skin lesions, brain tumor MRI diagnosis, X-Ray for chest analysis, Breast cancer using MRI imaging...
October 2018: Current Medical Imaging Reviews
https://www.readbyqxmd.com/read/30529218/machine-learning-integration-of-ct-histogram-analysis-to-evaluate-the-composition-of-atherosclerotic-plaques-validation-with-ib-ivus
#2
Takanori Masuda, Takeshi Nakaura, Yoshinori Funama, Tomokazu Okimoto, Tomoyasu Sato, Toru Higaki, Noritaka Noda, Naoyuki Imada, Yasutaka Baba, Kazuo Awai
BACKGROUND: To determine whether machine learning with histogram analysis of coronary CT angiography (CCTA) yields higher diagnostic performance for coronary plaque characterization than the conventional cut-off method using the median CT number. METHODS: We included 78 patients with 78 coronary plaques who had undergone CCTA and integrated backscatter intravascular ultrasound (IB-IVUS) studies. IB-IVUS diagnosed 32 as fibrous- and 46 as fatty or fibro-fatty plaques...
October 21, 2018: Journal of Cardiovascular Computed Tomography
https://www.readbyqxmd.com/read/30528325/carburization-level-identification-in-industrial-hp-pipes-using-ultrasonic-evaluation-and-machine-learning
#3
Lucas F M Rodrigues, Fábio C Cruz, Moisés A Oliveira, Eduardo F Simas Filho, Maria C S Albuquerque, Ivan C Silva, Cláudia T T Farias
Ultrasound nondestructive testing is commonly applied in industry to guarantee structural integrity. HP steel pyrolysis furnaces are used in petrochemical industry for lightweight hydrocarbon production. HP steel chromium content may be reduced in high-temperatures due to carbon diffusion. This characterizes the carburization phenomenon, which modifies magnetic properties, reduces mechanical resistance and may lead to structural rupture. For safe operation it is required to frequently determine carburizing level in pyrolysis furnace pipes...
October 10, 2018: Ultrasonics
https://www.readbyqxmd.com/read/30505345/intensive-care-unit-physician-delivered-point-of-care-renal-tract-ultrasound-in-acute-kidney-injury-is-feasible
#4
Prashant Parulekar, Ed Neil-Gallacher, Alex Harrison
Acute kidney injury is common in critically ill patients, with ultrasound recommended to exclude renal tract obstruction. Intensive care unit clinicians are skilled in acquiring and interpreting ultrasound examinations. Intensive Care Medicine Trainees wish to learn renal tract ultrasound. We sought to demonstrate that intensive care unit clinicians can competently perform renal tract ultrasound on critically ill patients. Thirty patients with acute kidney injury were scanned by two intensive care unit physicians using a standard intensive care unit ultrasound machine...
November 2018: Journal of the Intensive Care Society
https://www.readbyqxmd.com/read/30473474/computer-aided-diagnosis-of-congenital-abnormalities-of-the-kidney-and-urinary-tract-in-children-based-on-ultrasound-imaging-data-by-integrating-texture-image-features-and-deep-transfer-learning-image-features
#5
Q Zheng, S L Furth, G E Tasian, Y Fan
INTRODUCTION: Anatomic characteristics of kidneys derived from ultrasound images are potential biomarkers of children with congenital abnormalities of the kidney and urinary tract (CAKUT), but current methods are limited by the lack of automated processes that accurately classify diseased and normal kidneys. OBJECTIVE: The objective of the study was to evaluate the diagnostic performance of deep transfer learning techniques to classify kidneys of normal children and those with CAKUT...
October 31, 2018: Journal of Pediatric Urology
https://www.readbyqxmd.com/read/30441060/automated-myocardial-wall-motion-classification-using-handcrafted-features-vs-a-deep-cnn-based-mapping
#6
Hasmila A Omar, Arijit Patra, Joao S Domingos, Paul Leeson, Alison J Noblel
Compared to other modalities such as computed tomography or magnetic resonance imaging, the appearance of ultrasound images is highly dependent on the expertise of the sonographer or clinician making the image acquisition, as well as the machine used, making it a challenge to analyze due to the frequent presence of artefacts, missing boundaries, attenuation, shadows, and speckle. In addition, manual contouring of the epicardial and endocardial walls exhibits large inconsistencies and variations as it is strongly dependent on the sonographer's training and expertise...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/30441056/b-mode-ultrasound-based-diagnosis-of-liver-cancer-with-ceus-images-as-privileged-information
#7
Fanqing Meng, Jun Shi, Bangming Gong, Qi Zhang, Lehang Guo, Dan Wang, Huixiong Xu
Contrast-enhanced ultrasound (CEUS) is a valuable imaging modality for diagnosis of liver cancers. However, the complexity of CEUS-based diagnosis limits its wide application, and the B-mode ultrasound (BUS) is still the most popular diagnosis modality in clinical practice. In order to promote BUS-based computer-aided diagnosis (CAD) for liver cancers, we propose a learning using privileged information (LUPI) based CAD with BUS as the diagnosis modality and CEUS as PI. Particularly, the multimodal restricted Boltzmann machine (MRBM) works as a LUPI paradigm...
July 2018: Conference Proceedings: Annual International Conference of the IEEE Engineering in Medicine and Biology Society
https://www.readbyqxmd.com/read/30426362/automated-detection-of-vulnerable-plaque-in-intravascular-ultrasound-images
#8
Tae Joon Jun, Soo-Jin Kang, June-Goo Lee, Jihoon Kweon, Wonjun Na, Daeyoun Kang, Dohyeun Kim, Daeyoung Kim, Young-Hak Kim
Acute coronary syndrome (ACS) is a syndrome caused by a decrease in blood flow in the coronary arteries. The ACS is usually related to coronary thrombosis and is primarily caused by plaque rupture followed by plaque erosion and calcified nodule. Thin-cap fibroatheroma (TCFA) is known to be the most similar lesion morphologically to a plaque rupture. In this paper, we propose methods to classify TCFA using various machine learning classifiers including feed-forward neural network (FNN), K-nearest neighbor (KNN), random forest (RF), and convolutional neural network (CNN) to figure out a classifier that shows optimal TCFA classification accuracy...
November 14, 2018: Medical & Biological Engineering & Computing
https://www.readbyqxmd.com/read/30391224/using-a-natural-language-processing-and-machine-learning-algorithm-program-to-analyze-inter-radiologist-report-style-variation-and-compare-variation-between-radiologists-when-using-highly-structured-versus-more-free-text-reporting
#9
Lane F Donnelly, Robert Grzeszczuk, Carolina V Guimaraes, Wei Zhang, George S Bisset Iii
PURPOSE: To use a natural language processing and machine learning algorithm to evaluate inter-radiologist report variation and compare variation between radiologists using highly structured versus more free text reporting. MATERIALS AND METHODS: 28,615 radiology reports were analyzed for 4 metrics: verbosity, observational terms only, unwarranted negative findings, and repeated language in different sections. Radiology reports for two imaging examinations were analyzed and compared - one which was more templated (ultrasound - appendicitis) and one which relied on more free text (chest radiograph - single view)...
October 9, 2018: Current Problems in Diagnostic Radiology
https://www.readbyqxmd.com/read/30381856/artificial-intelligence-and-amniotic-fluid-multiomics-analysis-the-prediction-of-perinatal-outcome-in-asymptomatic-short-cervix
#10
Ray O Bahado-Singh, Jiri Sonek, David McKenna, David Cool, Buket Aydas, Onur Turkoglu, Trent Bjorndahl, Rupasri Mandal, David Wishart, Perry Friedman, Stewart F Graham, Ali Yilmaz
OBJECTIVE: To evaluate the utility of Artificial Intelligence i.e. Deep Learning (DL) and other machine learning techniques for the prediction of important pregnancy outcomes in asymptomatic short cervical length (CL). METHOD: The amniotic fluid (AF) had been obtained from second trimester patients with asymptomatic women with short cervical length (<15 mm). CL, funneling and the presence of AF 'sludge' were assessed in all cases. Combined targeted metabolomic and proteomic analysis of amniotic fluid (AF) was performed...
October 31, 2018: Ultrasound in Obstetrics & Gynecology
https://www.readbyqxmd.com/read/30374980/automatic-tumor-segmentation-in-breast-ultrasound-images-using-a-dilated-fully-convolutional-network-combined-with-an-active-contour-model
#11
Yuzhou Hu, Yi Guo, Yuanyuan Wang, Jinhua Yu, Jiawei Li, Shichong Zhou, Cai Chang
PURPOSE: Due to the low contrast, blurry boundaries, and large amount of shadows in breast ultrasound (BUS) images, automatic tumor segmentation remains a challenging task. Deep learning provides a solution to this problem, since it can effectively extract representative features from lesions and the background in BUS images. METHODS: A novel automatic tumor segmentation method is proposed by combining a dilated fully convolutional network (DFCN) with a phase-based active contour (PBAC) model...
October 29, 2018: Medical Physics
https://www.readbyqxmd.com/read/30356808/diagnostic-point-of-care-ultrasound-pocus-for-gastrointestinal-pathology-state-of-the-art-from-basics-to-advanced
#12
REVIEW
Fikri M Abu-Zidan, Arif Alper Cevik
The use of point-of-care ultrasound (POCUS) by non-radiologists has dramatically increased. POCUS is completely different from the routine radiological studies. POCUS is a Physiological, On spot, extension of the Clinical examination, that is Unique, and Safe. This review aims to lay the basic principles of using POCUS in diagnosing intestinal pathologies so as to encourage acute care physicians to learn and master this important tool. It will be a useful primer for clinicians who want to introduce POCUS into their clinical practice...
2018: World Journal of Emergency Surgery: WJES
https://www.readbyqxmd.com/read/30345104/clinical-implication-of-the-innovations-of-the-8-th-edition-of-the-tnm-classification-for-esophageal-and-esophago-gastric-cancer
#13
EDITORIAL
Xavier Benoit D'Journo
Epidemiology of esophageal cancer and esophagogastric junction (EGJ) has deeply changed for the past two decades with a dramatically increase of adenocarcinoma whereas squamous cell carcinoma (SCC) has slowly decreased. Moreover, the two histological types differ in a number of features including risks factors, tumor location, tumor biology and outcomes. In acknowledgement of these differences, the newest 8th edition of the American Joint Committee on Cancer (AJCC) tumor, node and metastasis (TNM) staging classification of epithelial cancers of the esophagus and EGJ has refined this histology-specific disease stage with incorporation of new anatomic and non-anatomic categories...
August 2018: Journal of Thoracic Disease
https://www.readbyqxmd.com/read/30344990/evaluation-of-commonly-used-algorithms-for-thyroid-ultrasound-images-segmentation-and-improvement-using-machine-learning-approaches
#14
Prabal Poudel, Alfredo Illanes, Debdoot Sheet, Michael Friebe
The thyroid is one of the largest endocrine glands in the human body, which is involved in several body mechanisms like controlling protein synthesis and the body's sensitivity to other hormones and use of energy sources. Hence, it is of prime importance to track the shape and size of thyroid over time in order to evaluate its state. Thyroid segmentation and volume computation are important tools that can be used for thyroid state tracking assessment. Most of the proposed approaches are not automatic and require long time to correctly segment the thyroid...
2018: Journal of Healthcare Engineering
https://www.readbyqxmd.com/read/30343454/machine-learning-for-diagnostic-ultrasound-of-triple-negative-breast-cancer
#15
Tong Wu, Laith R Sultan, Jiawei Tian, Theodore W Cary, Chandra M Sehgal
PURPOSE: Early diagnosis of triple-negative (TN) breast cancer is important due to its aggressive biological characteristics, poor clinical outcomes, and limited options for therapy. The goal of this study is to evaluate the potential of machine learning with quantitative ultrasound image features for the diagnosis of TN breast cancer. METHODS: Ultrasonic and clinical data of 140 surgically confirmed breast cancer cases were analyzed retrospectively for the diagnosis of TN and non-TN (NTN) subtypes...
October 20, 2018: Breast Cancer Research and Treatment
https://www.readbyqxmd.com/read/30342682/extraction-of-bi-rads-findings-from-breast-ultrasound-reports-in-chinese-using-deep-learning-approaches
#16
Shumei Miao, Tingyu Xu, Yonghui Wu, Hui Xie, Jingqi Wang, Shenqi Jing, Yaoyun Zhang, Xiaoliang Zhang, Yinshuang Yang, Xin Zhang, Tao Shan, Li Wang, Hua Xu, Shui Wang, Yun Liu
BACKGROUND: The wide adoption of electronic health record systems (EHRs) in hospitals in China has made large amounts of data available for clinical research including breast cancer. Unfortunately, much of detailed clinical information is embedded in clinical narratives e.g., breast radiology reports. The American College of Radiology (ACR) has developed a Breast Imaging Reporting and Data System (BI-RADS) to standardize the clinical findings from breast radiology reports. OBJECTIVES: This study aims to develop natural language processing (NLP) methods to extract BI-RADS findings from breast ultrasound reports in Chinese, thus to support clinical operation and breast cancer research in China...
November 2018: International Journal of Medical Informatics
https://www.readbyqxmd.com/read/30335753/visual-assessment-versus-computer-assisted-gray-scale-analysis-in-the-ultrasound-evaluation-of-neonatal-respiratory-status
#17
Francesco Raimondi, Fiorella Migliaro, Luisa Verdoliva, Diego Gragnaniello, Giovanni Poggi, Roberta Kosova, Carlo Sansone, Gianfranco Vallone, Letizia Capasso
BACKGROUND AND AIM: Lung ultrasound has been used to describe common respiratory diseases both by visual and computer-assisted gray scale analysis. In the present paper, we compare both methods in assessing neonatal respiratory status keeping two oxygenation indexes as standards. PATIENTS AND METHODS: Neonates admitted to the NICU for respiratory distress were enrolled. Two neonatologists not attending the patients performed a lung scan, built a single frame database and rated the images with a standardized score...
2018: PloS One
https://www.readbyqxmd.com/read/30226815/machine-learning-based-automatic-identification-of-fetal-abdominal-circumference-from-ultrasound-images
#18
Bukweon Kim, Kang Cheol Kim, Yejin Park, Ja-Young Kwon, Jaeseong Jang, Jin Keun Seo
OBJECTIVE: Obstetricians mainly use ultrasound imaging for fetal biometric measurements. However, such measurements are cumbersome. Hence, there is urgent need for automatic biometric estimation. Automated analysis of ultrasound images is complicated owing to the patient-specific, operator-dependent, and machine-specific characteristics of such images. APPROACH: This paper proposes a method for the automatic fetal biometry estimation from 2D ultrasound data through several processes consisting of a specially designed convolutional neural network (CNN) and U-Net for each process...
October 22, 2018: Physiological Measurement
https://www.readbyqxmd.com/read/30178143/multiparametric-ultrasomics-of-significant-liver-fibrosis-a-machine-learning-based-analysis
#19
Wei Li, Yang Huang, Bo-Wen Zhuang, Guang-Jian Liu, Hang-Tong Hu, Xin Li, Jin-Yu Liang, Zhu Wang, Xiao-Wen Huang, Chu-Qing Zhang, Si-Min Ruan, Xiao-Yan Xie, Ming Kuang, Ming-De Lu, Li-Da Chen, Wei Wang
OBJECTIVE: To assess significant liver fibrosis by multiparametric ultrasomics data using machine learning. MATERIALS AND METHODS: This prospective study consisted of 144 patients with chronic hepatitis B. Ultrasomics-high-throughput quantitative data from ultrasound imaging of liver fibrosis-were generated using conventional radiomics, original radiofrequency (ORF) and contrast-enhanced micro-flow (CEMF) features. Three categories of features were explored using pairwise correlation and hierarchical clustering...
September 3, 2018: European Radiology
https://www.readbyqxmd.com/read/30149250/calcium-detection-its-quantification-and-grayscale-morphology-based-risk-stratification-using-machine-learning-in-multimodality-big-data-coronary-and-carotid-scans-a-review
#20
REVIEW
Sumit K Banchhor, Narendra D Londhe, Tadashi Araki, Luca Saba, Petia Radeva, Narendra N Khanna, Jasjit S Suri
PURPOSE OF REVIEW: Atherosclerosis is the leading cause of cardiovascular disease (CVD) and stroke. Typically, atherosclerotic calcium is found during the mature stage of the atherosclerosis disease. It is therefore often a challenge to identify and quantify the calcium. This is due to the presence of multiple components of plaque buildup in the arterial walls. The American College of Cardiology/American Heart Association guidelines point to the importance of calcium in the coronary and carotid arteries and further recommend its quantification for the prevention of heart disease...
October 1, 2018: Computers in Biology and Medicine
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