An introductory video into diagnostic radiography and medical imaging for the uninitiated. Want to learn more? SoR aka Society of Radiographers https://www.sor.org/ Health Careers https://www.healthcareers.nhs.uk/explore-roles/allied-health-professionals/radiographer-diagnostic Royal College of Radiologists, a Historical Timeline of X-Rays and Radiology https://www.rcr.ac.uk/college/about-college/history-college/historical-timeline#1 UCAS Current Universities Offering Radiography http://search.ucas.com/search/providers?Vac=1&AvailableIn=2017&Query=Diagnostic%20Radiography Some generally cool stuff: How fast does a CT scanner spin…? https://www.youtube.com/watch?v=2CWpZKuy-NE Quite Fast Wiki-Radiography http://www.wikiradiography.net/ Radiopedia https://radiopaedia.org/ Radiology Masterclass http://www.radiologymasterclass.co.uk/ This is my first venture into making educational videos on YouTube in relation to Radiography. I know there’s gonna be teething problems so bear with me. Feel free to leave a comment on what you’d like to see next. I am thinking maybe split up the videos more. I’ve also come to realise how much stuff there is to learn about during the degree. ------------------------------------------------------------------------------------------------------------------------------------- Disclaimer: I will try my best to answer any questions relating to radiography, however if it a medical question relating directly to your own health this video and associated content is not a replacement for seeing an actual doctor.
Views: 18252 Stevone
New Deep Learning Techniques 2018 "Deep learning in medical imaging: Techniques for image reconstruction, super-resolution and segmentation" Daniel Rueckert, Imperial College London Abstract: This talk will introduce framework for reconstructing MR images from undersampled data using a deep cascade of convolutional neural networks to accelerate the data acquisition process. We show that such a method can outperforms state-of-the-art compressed sensing approaches, such as dictionary learning-based MRI (DLMRI) reconstruction, both in terms of image quality and reconstruction speed. We will also discuss image super-resolution approaches that are based on residual CNNs and which can reconstruct high resolution 3D volumes from 2D image stacks for more accurate image analysis and visualisation. In addition, we will present neural networks for medical image segmentation. More specifically, we will discuss unsupervised domain adaptation using adversarial neural networks to train a segmentation method which is more invariant to differences in the input data (across different scanners and acquisition protocols), and which does not require any annotations on the test domain. Finally, the talk will ensemble methods for segmentation, (Ensembles of Multiple Models and Architectures – EMMA) which provide robust performance through aggregation of predictions from a wide range of methods. EMMA can be seen as an unbiased, generic deep learning model which is shown to yield excellent performance, winning the first position in the BRATS 2017 competition among 50+ participating teams. Institute for Pure and Applied Mathematics, UCLA February 6, 2018 For more information: http://www.ipam.ucla.edu/programs/workshops/new-deep-learning-techniques/?tab=overview
Views: 3105 Institute for Pure & Applied Mathematics (IPAM)
(Visit: http://www.uctv.tv/) Improvements in diagnostic imaging – US, CT, MRI, PET – have been spectacular and the use of imaging has soared over the last two decades driven by a combination of patient and physician demand. Dr. Rebecca Smith‐BindmanIs looks at the potential harm associated with radiation exposure and what you should do about it. Recorded on 02/23/2016. Series: "UCSF Osher Center for Integrative Medicine presents Mini Medical School for the Public" [4/2016] [Health and Medicine] [Show ID: 30672]
Views: 2405 University of California Television (UCTV)
Ultrasound orientation & imaging planes explained clearly by point-of-care ultrasound expert Joshua Jacquet, MD of https://www.medcram.com Ultrasound is EXPLODING in popularity among medical professionals & clinicians...and for good reason. Quite simply, ultrasound often makes diagnosing medical problems & performing procedures faster, safer & more cost effective. Physicians, nurse practitioners, physician assistants, nurses, technicians & other professionals can benefit from ultrasound in almost every medical setting & specialty Ultrasound that is performed by the clinician, at the bedside, is called many names: clinical ultrasound, bedside ultrasound, & point of care ultrasound (POCUS). MedCram.com Instructor & Ultrasound expert Dr. Jacquet illustrates a key skill in this video: How to orient the ultrasound probe with what is seen on screen and understand the associated imaging planes. Dr. Jacquet recently joined the MedCram team and we've launched the first of several "Ultrasound Principles & Instrumentation Explained Clearly" courses. Master the foundations of bedside ultrasound/point-of-care ultrasound (POCUS) with this course available here: https://www.medcram.com/courses/clinical-bedside-ultrasound Learn the many advantages and possibilities medical ultrasound offers. Dr. Jacquet's course Ultrasound Principles & Instrumentation includes: - A clear understanding of the physics of ultrasound waves & and how they react in tissue. - An overview of ultrasound transducers and what they're used for. - Key ultrasound terminology, orientation, imaging planes, and biosafety. - Step by step illustrations of the nobs, dials, and modes of an ultrasound machine ("knobology"). - Examples of various ultrasound artifacts that impact ultrasound images. - How to handle an ultrasound transducer and set up the machine for your first ultrasound exam. Visit https://www.MedCram.com for top rated medical courses and over 100 free lectures. MedCram: Medical education topics explained clearly including: Respiratory lectures such as Asthma and COPD. Renal lectures on Acute Renal Failure and Adrenal Gland. Internal medicine videos on Oxygen Hemoglobin Dissociation Curve and Medical Acid Base. A growing library on critical care topics such as Shock, Diabetic Ketoacidosis (DKA), and Mechanical Ventilation. Cardiology videos on Hypertension, ECG / EKG Interpretation, and heart failure. VQ Mismatch and Hyponatremia lectures have been popular among medical students and physicians. The Pulmonary Function Tests (PFTs) videos and Ventilator-associated pneumonia bundles and lectures have been particularly popular with RTs. NPs and PAs have given great feedback on Pneumonia Treatment and Liver Function Tests among many others. Many nursing students have found the Asthma and shock lectures very helpful. We're starting a new course series on clinical ultrasound / ultrasound medical imaging. Recommended Audience - medical professionals and medical students: including physicians, nurse practitioners, physician assistants, nurses, respiratory therapists, EMT and paramedics, and many others. Review and test prep for USMLE, MCAT, PANCE, NCLEX, NAPLEX, NBDE, RN, RT, MD, DO, PA, NP school and board examinations. More from MedCram.com medical videos: MedCram Website: https://www.medcram.com Facebook: https://www.facebook.com/MedCram Google+: https://plus.google.com/u/1/+Medcram Twitter: https://twitter.com/MedCramVideos Subscribe to the official MedCram.com YouTube Channel: https://www.youtube.com/subscription_center?add_user=medcramvideos Produced by Kyle Allred PA-C Please note: MedCram medical videos, medical lectures, medical illustrations, and medical animations are for medical education and exam preparation purposes, and not intended to replace recommendations by your doctor or health care provider.
Views: 72693 MedCram - Medical Lectures Explained CLEARLY
PyData Tel Aviv Meetup #15 23 July 2018 Sponsored and Hosted by Taboola https://www.meetup.com/PyData-Tel-Aviv/ Even though Deep Learning has been very popular in Computer Vision community already since 2012, only in the last years it gained popularity also in the medical imaging domain. In this talk I will present the unique challenges in the medical imaging domain, and how they can be addressed. We will take image segmentation as an example and see the evolution of solutions for this problem. www.pydata.org PyData is an educational program of NumFOCUS, a 501(c)3 non-profit organization in the United States. PyData provides a forum for the international community of users and developers of data analysis tools to share ideas and learn from each other. The global PyData network promotes discussion of best practices, new approaches, and emerging technologies for data management, processing, analytics, and visualization. PyData communities approach data science using many languages, including (but not limited to) Python, Julia, and R. Find a PyData chapter near you: meetup.com/pro/pydata
Views: 997 PyData
Visit us - https://QuantumUniversity.com Quantum physics explains the nature and behavior of matter and energy on the atomic and subatomic level. It explains from the smallest particle how the entire universe works. The scientific discoveries fundamentally change how we perceive our entire reality. From the fastest computers in the world to your every day grocery store scanner, the application of quantum physics is at the leading edge of modern technology today. The language of quantum physics helps us to better understand integrative medicine. Various alternative healing modalities from both ancient and modern medical traditions become as logical, elegant, and satisfying as the interpretation of quantum physics itself. Quantum physics proposes consciousness as the fabric of reality. It is a model for a deeper understanding of the universe. And consequently, the art of healing. With an in-depth knowledge of the gifts of quantum physics to medicine, we are better equipped to prevent disease and promote optimal health for every human being in the world. One of the great challenges within the current model of medicine is to break free of the traditional linear ways of thinking. Doctors and medical schools continue to use Newtonian physics, perpetuating a materialistic approach to healing. #QuantumUniversity has stepped into a new paradigm. Using the principles of quantum physics to explain how healing takes place. Our education is transformed by a vision of achieving full potentiality for health and an expanded understanding of our reality. The field and consciousness itself. Merging quantum physics with various modalities of integrative medicine creates solutions that address imbalances in the body, mind, and spirit, to achieve optimal health. Students and graduates gain a better understanding of health and disease and how the body, mind, and subtle energies all need to be addressed for optimal healing. Quantum University brings world class educators and leaders together to create an innovative, unique, curriculum. Dr. Paul Drouin, M.D., founder and professor of integrative medicine, says, "My objective in creating Quantum University was to add the missing pieces of the puzzle of how healing occurs." Teaching integrative medicine based on quantum physics is our role at quantum university. We are creating the future model of medicine, one student at a time. ⭐Learn more about Quantum University ⭐ 🎓Degree Programs Offered - https://quantumuniversity.com/degree-programs/ 💻Student Experience - https://quantumuniversity.com/student-experience/ 💙Career Paths - https://quantumuniversity.com/career-paths/ ❓ Request Information - https://quantumuniversity.com/request-information/ 👍 Like Us on Facebook - https://www.facebook.com/QuantumUniversity
Views: 4488 Quantum University
The Avon Foundation Breast Imaging Center at NewYork-Presbyterian/Columbia University Medical Center is a dedicated screening facility offering state-of-the-art imaging services in a supportive, private, and comfortable setting. Our staff schedules appointments quickly and efficiently and ensures that you are provided with your results as soon as possible. For more information, please visit: http://nyp.org/services/avon.html
Views: 3948 NewYork-Presbyterian Hospital
This brief video tutorial discusses the anatomical position, directional terms and planes/sections. The focus for planes/sections are in the context of radiographic imaging. - Anatomical position (0:17-2:37) - Directional terms of position (2:37-9:15) - Planes and Sections (9:15-18:46) - Intro to anatomy in a nutshell (18:46-19:05)
Views: 12651 The Noted Anatomist
Rev. Steve Munz gives a series of lectures and discussions on the Biblical framework of medicine. This series was a part of Summer Medical Institute Philladelphia 2011. smiphilly.wordpress.com
Views: 34 Dan Mirsch
Learn about new methods using computer-aided diagnosis algo¬rithms that are being developed for a broad range of diseases, organs, and imaging modalities. This talk will present highlights of the history of radiological imaging and the challenges facing the developers of new applications in medical imaging. She is a Fellow of the Optical Society of America and American Institute for Medical Biological Engineering. Dr. Kyle Myers is the coauthor, with Harrison H. Barrett, of the book Foundations of Imaging Science, published and winner of the First Biennial J.W. Goodman Book Writing Award from Optical Society of America and American Institute for Medical Biological Engineering.
Views: 4567 Distinctive Voices
Dr. Michael Mahoney is a professor at the University of California, Berkeley. In this recording, he presents a web lecture titled, “Biomedicine & the Foundations of Data?.” Video Description Recent technological advances have permitted the generation of enormous quantities of data in a wide range of application domains, from the social sciences and social media to electronic and traditional commerce to the physical and biomedical sciences. This has in turn generated interest in foundational issues. Examples of such issues are to understand what is common and what is distinct between data in each of these areas and methods applied to data from each of these areas, to address theoretical questions underlying machine learning and data analysis tools, and to ask what does it even mean to provide a foundation for an area as diverse as what is currently called data science. Dr. Mahoney will address some of these questions, including how biomedicine may fit within this area. He will provide a "test case" example of how work on foundational topics has been applied to biomedical problems: the development of algorithmically and statistically principled and interpretable low-rank matrix decompositions and how they can then be implemented and applied to terabytes of data to solve very practical genetics and medical imaging problems. He will then conclude by describing some challenges and opportunities. About the Speaker Michael W. Mahoney is at the University of California at Berkeley in the Department of Statistics and at the International Computer Science Institute (ICSI). He works on algorithmic and statistical aspects of modern large-scale data analysis. Much of his recent research has focused on large-scale machine learning, including randomized matrix algorithms and randomized numerical linear algebra, geometric network analysis tools for structure extraction in large informatics graphs, scalable implicit regularization methods, and applications in genetics, astronomy, medical imaging, social network analysis, and internet data analysis. He received his PhD from Yale University with a dissertation in computational statistical mechanics, and he has worked and taught at Yale University in the mathematics department, at Yahoo Research, and at Stanford University in the mathematics department. Among other things, he is on the national advisory committee of the Statistical and Applied Mathematical Sciences Institute (SAMSI), he was on the National Research Council's Committee on the Analysis of Massive Data, he co-organized the Simons Institute's Fall 2013 program on the Theoretical Foundations of Big Data Analysis, and he runs the biennial MMDS Workshops on Algorithms for Modern Massive Data Sets. He is currently running the NSF/TRIPODS-funded FODA (Foundations of Data Analysis) Institute at UC Berkeley. View slides from this lecture: Coming soon… Visit our webpage to view archived videos covering various topics in data science: https://bigdatau.ini.usc.edu/data-science-seminars
Dr. Ebraheim’s educational animated video demonstrates how radiation affects the body, the different types of radiology procedures, and safety recommendations. X-rays ionize human tissue and deposit energy that can cause harmful changes within the body (break the DNA chain). There is a cancer risk from X-rays. The dose of radiation is cumulative. X-rays are considered for carcinogen list. The government is attempting to avoid the use of unnecessary CT scans and x-rays to avoid unnecessary exposure to radiation. This highlights the cancer risk. Doctors need to pay close attention to the risks involved with the use of x-rays. The cancer risk associated with radiation exposure is documented in cases of atomic bomb survivors. The risk for medical uses is controversial and usually played down by physicians. Radiation at a high level is carcinogenic. The level of radiation from x-ray exposure is low. The effects of low-level radiation is not known. What is the safe radiation level? The safe level is not known. It is known that CT scans, fluoroscopy, mammography and x-rays expose the public to high levels of radiation especially in young females. The risk of exposure should balance the medical benefit. Optimize radiation doses by exposing the patient only to enough radiation to get a clear image. There is a growing concern about the risk associated with giving patient large doses of radiation. The use of CT scans has increased recently in adults and children possibly exposing the patient to an unnecessarily high dose of radiation. CT scan is the method often used to diagnose cancer, diseases fractures and it exposes the patient to a much larger does of radiation than x-rays. Radiation from CT scan of the pelvis equals the same amount as 100 chest x-rays. Children are ten times more sensitive to radiation than adults. 3-4 million children receive CT scans and about 1,500 of them will develop cancer two decades later. Children should not be given an adult dose of radiation. Radiation dose limits: CT scan of the pelvis has the highest level of exposure to the skin, marrow and gonads. Use mini fluoroscopy C-arm whenever possible. Fluoroscopy emits a lot of radiation. The closer the extremity is to the radiation source, the higher the dose of radiation the patient receives. When the distance from the beam increases, the dose of radiation is less. Attempt to decrease exposure time. Radiation intensity follows the inverse square law. It is all about distance. If the intensity of radiation at 1 meter from the source is 100 mR/hr then the intensity of radiation at 2 meters from the source is ¼ or 25 mR/hr in same unit area. At 3 meters from the source, the intensity of radiation is 1/9 the original or 11.1 mR/hr. Units of radiation (radiation nomenclature) •Roentgen: unit of radiation exposure in air. •Rad: energy absorbed per gram of tissue. •Rem: biological effect of a rad. There is less exposure to the physician when imaging a smaller body part. Larger body parts create an increased exposure to the physician when imaging a patient with C-arm. Do not be in the direct path of the radiation beam. Protection: •Monitoring: a dosimeter badge only records how much radiation you have received. It does not protect you from exposure to radiation. •Shielding: lead gowns and aprons work to stop exposure to fluoroscopy radiation. Lead aprons attenuate scattered radiation by about 95%. •Position Rapidly dividing cells are most sensitive to radiation exposure: sperms, lymphocytes, small intestine, and stomach. Radiation damage seldom appears at the time of radiation. The first effects of radiation damage is usually seen as a drop in the white blood cell count. The first external sign of damage is seen as a skin burn. Studies suggest that people who use fluoroscopy extensively have a higher rate of cataracts. Early effects or radiation exposure: •Death •Hematological depression •Chromosome aberration •Skin erythema •Epilation. Team exposure to radiation •Direct beam 4,000 mrem/min •Surgeon (1 ft.): 20 mrem/min whole body •First assist (2 ft.): 6 mrem/min whole body •No exposure (5 ft.) at scrub or anesthesiologist. •6 feet is safe. Become a friend on facebook: http://www.facebook.com/drebraheim Follow me on twitter: https://twitter.com/#!/DrEbraheim_UTMC Donate to the University of Toledo Foundation Department of Orthopaedic Surgery Endowed Chair Fund: https://www.utfoundation.org/foundation/home/Give_Online.aspx?sig=29
Views: 72959 nabil ebraheim
The principles of MRI to the tune of Tubthumping by Chumbawamba. Class project for BME258--Foundations of Medical Imaging at Vanderbilt University
Views: 303 superrainbowchicken
This presentation explains the basic principle behind Digital Radiography and its types used in Diagnostic Imaging. Every medical imaging, radiography and radio-diagnosis students must watch it once. I would be grateful to get your valuable comments.
Views: 1216 Surendra Maharjan
(5 Jul 2018) LEADIN Artifical Intelligence has defeated a group of human doctors in a neuroimaging competition in Beijing. In two rounds of competition, contestants raced to diagnose brain conditions by interpreting CT and MRI images. But the human doctors say there's still a lot for AI to learn. STORYLINE This is the world's first competition between physicians and artificial intelligence in neuroimaging. Human medics competed against AI to diagnose brain tumours and predict haemorrhage and cerebrovascular diseases by studying images of over 200 cases within the required time. The human team of 30 radiologists and neurological doctors lost to the neurological disease diagnostic AI system called BioMind. In both rounds the AI was 20 percent more accurate. BioMind was devised in the lab that was set up by the China National Clinical Research Center and Hanalytics Artificial Intelligence Research Centre for Neurological Diseases in the Beijing Tiantan Hospital, which specialises in treatment for neurological conditions. Developed with deep learning (machine based learning), BioMind was trained with tens of thousands of CT and MRI images of neurological disorder cases that were archived by Beijing Tiantan Hospital in the past decade to teach the system to recognize brain-related diseases on images and produce a preliminary diagnosis as the reference for doctors. The AI system aims at assisting doctors to reduce blind spots and misdiagnosis, and increasing doctors' efficiency, says Raymond Moh, CEO of Hanalytics. "The entire process of diagnosis can take half an hour to close an hour to analyze thousands of images just for one patient alone. But the whole process can be automated all within a few seconds with artificial intelligence," Moh says. However Jing Lina, a radiologist from Beijing Tiantan Hospital on the losing human team, doubts the system could handle real-world complexities beyond the "either-or questions" of the competition. "There are situations where two similar images indicate two different pathological features. We were not given any information about patients' medical history, which we can use for comprehensive diagnosis. We have nothing but the MRI images," says Jing a member of the human diagnostic team. "One of the advantages that human doctors enjoy is that we have solid medical foundations and background with which we can make the comprehensive analysis. With all these information, I believe we have the chance to beat AI" Jing adds. The medical demands of China's enormous population have stressed the supply of trained doctors. The government has turned to AI for a solution. The State Council, China's chief administrative authority, in July 2017 issued the "Three-Year Action Plan for Promoting the Development of a New Generation of Artificial Intelligence (2018-2020)", which proposed to establish a fast and accurate AI application system in medical care to upgrade medical service. In this country, every year, there is 40 percent increase of medical images. But the increment of radiologists is less than five percent. This gap is going to increase. You will never be able to address (the issue) by traditional IT solution. So AI is probably one of the only solution to close this gap. The problem is there is not enough radiologists and doctors to start with to be replaced, rather, AI itself is to fill this gap" says Moh. BioMind has achieved an accuracy rate of around 90 percent in the diagnosis of common neurological diseases. Find out more about AP Archive: http://www.aparchive.com/HowWeWork Twitter: https://twitter.com/AP_Archive Facebook: https://www.facebook.com/APArchives Google+: https://plus.google.com/b/102011028589719587178/+APArchive Tumblr: https://aparchives.tumblr.com/ Instagram: https://www.instagram.com/APNews/ You can license this story through AP Archive: http://www.aparchive.com/metadata/youtube/1217bbbfbcaae9066fd5a391873ed034
Views: 1094 AP Archive
Overview of the various ways that medical professionals are using clinical/ bedside ultrasound (also known as point-of-care ultrasound), and reasons more clinicians should consider its use. Dr. Seheult of MedCram.com interviews clinical ultrasound expert Dr. Jacquet on bedside ultrasound including: - What is "clinical ultrasound" and is it any different than bedside ultrasound or point of care ultrasound? - Medical specialties and professionals who are using clinical ultrasound (Physicians, nurses, nurse practitioners, PAs, RTs, ultrasound technicians, paramedics, etc.) - The huge diagnostic advantages bedside ultrasound gives clinicians. - Newer technologies in clinical sonography. - Is ultrasound difficult to learn, and what are next steps for those who want to make ultrasound part of their practice? Dr. Jacquet recently joined the MedCram team and we've launched the first of several "Clinical Ultrasound Explained Clearly" courses. The first course will help you master the foundations of bedside ultrasound and is available here: https://www.medcram.com/courses/clinical-bedside-ultrasound This course includes: - A clear understanding of the physics of ultrasound waves & and how they react in tissue. - An overview of ultrasound transducers and what they're used for. - Key ultrasound terminology, orientation, imaging planes, and biosafety. - Step by step illustrations of the nobs, dials, and modes of an ultrasound machine ("knobology"). - Examples of various ultrasound artifacts that impact ultrasound images. - How to handle an ultrasound transducer and set up the machine for your first ultrasound exam. Visit https://www.MedCram.com for top rated medical courses and over 100 free lectures. MedCram: Medical education topics explained clearly including: Respiratory lectures such as Asthma and COPD. Renal lectures on Acute Renal Failure and Adrenal Gland. Internal medicine videos on Oxygen Hemoglobin Dissociation Curve and Medical Acid Base. A growing library on critical care topics such as Shock, Diabetic Ketoacidosis (DKA), and Mechanical Ventilation. Cardiology videos on Hypertension, ECG / EKG Interpretation, and heart failure. VQ Mismatch and Hyponatremia lectures have been popular among medical students and physicians. The Pulmonary Function Tests (PFTs) videos and Ventilator-associated pneumonia bundles and lectures have been particularly popular with RTs. NPs and PAs have given great feedback on Pneumonia Treatment and Liver Function Tests among many others. Many nursing students have found the Asthma and shock lectures very helpful. We're starting a new course series on clinical ultrasound / ultrasound medical imaging. Recommended Audience - medical professionals and medical students: including physicians, nurse practitioners, physician assistants, nurses, respiratory therapists, EMT and paramedics, and many others. Review and test prep for USMLE, MCAT, PANCE, NCLEX, NAPLEX, NBDE, RN, RT, MD, DO, PA, NP school and board examinations. More from MedCram.com medical videos: MedCram Website: https://www.medcram.com Facebook: https://www.facebook.com/MedCram Google+: https://plus.google.com/u/1/+Medcram Twitter: https://twitter.com/MedCramVideos Subscribe to the official MedCram.com YouTube Channel: https://www.youtube.com/subscription_center?add_user=medcramvideos Produced by Kyle Allred PA-C Please note: MedCram medical videos, medical lectures, medical illustrations, and medical animations are for medical education and exam preparation purposes, and not intended to replace recommendations by your doctor or health care provider.
Views: 6839 MedCram - Medical Lectures Explained CLEARLY
From the AOCR Resident Distance Learning Lecture Series, this is a case conference/board review intended to focus on trauma in Interventional Radiology. This lecture is presented by Keri Conner, DO, who is the Chief of Interventional Radiology at the University of Oklahoma Health Sciences Center. This series is sponsored by the AOCR Education Foundation.
Views: 1290 AOCR Radiology
Our most recent research to obtain liver volume, hepatic vessels and Couinaud's liver representation from medical CT or MRI data.
Views: 157 Antoine Vacavant
Author: Bernard E. Bulwer, MD, MSc, RCS, FASE Boston, Massachusetts, USA BOOK LINK: https://www.amazon.com/gp/product/1721777970/ref=dbs_a_def_rwt_hsch_vapi_taft_p1_i5 AUTHOR PAGES: https://www.amazon.com/Bernard-E.-Bulwer/e/B001JPCKTO Transthoracic Echocardiography: Foundations of Image Acquisition and Interpretation- 2nd Edition, Publication: July 2018 (Print Version). 500 pages. Amazon Kindle Edition in progress. This book is a the most highly illustrated and practical tour de force on the essential foundations of optimal image acquisition and interpretation in adult transthoracic echocardiography. A foundation reference for cardiac sonographers, medical students, medical residents and fellows, specialists, and the medical imaging specialties. FEATURES: The most highly illustrated guide to the ASE-recommended standards nomenclature in adult transthoracic echocardiography. An expert foundation guide to the performance and interpretation of the adult transthoracic echocardiography examination. Fundamentals of echo-anatomy, echo-physiology, hemodynamics, basic physical principles of cardiac ultrasound, and the standard echocardiographic views. Over 2,000 insightful illustrations, images, infographics, and flow charts. WHAT’S NEW IN THE SECOND EDITION Greatly expanded Reference Guide, with updated Figures and Tables. Includes the most recent ASE/EACVI guidelines on chamber quantification, using highly illustrated formats.
Views: 47 Echo Stethoscope Academy
James W. Backstrom, MD, Chief Medical Officer for Foundation Radiology Group. ALARA: As Low As Reasonably Achievable is a concept that began in the pediatric imaging community but has now advanced to be a vital component of progressive Radiology Departments around the country. Physicians are taught to "do no harm" as a cornerstone to patient care delivery. Radiation, if utilized without careful attention to technique can indeed add future risk to patients. This fact must be weighed against the significant benefits that advanced Radiology has added to the diagnostic abilities of clinicians. The pursuit of "prettier" pictures is no longer viewed as the ultimate goal for the ALARA conscious physician---getting the diagnosis with the lowest possible radiation exposure is now the mantra. We hope this lecture will allow you to serve as a proactive patient care advocate in the diagnostic radiology arena of a state of the art radiology department.
Views: 1887 FoundationRad
We had some young visitors in our Diagnostic Imaging Department to show our communities what happens when you come to South Bruce Grey Health Centre for a CT scan. Thank you for supporting the fundraising efforts of our local hospital foundations for our new CT scanner! #ComeTogether
Views: 182 SBGHealthCentre
Your role as an informatics professional is a unique blend of technical, clinical and business skills. This practice field is expanding throughout the healthcare enterprise. The ability to master the skill set, orchestrate a complex set of functions, and build cross-disciplinary teams are key elements for career success in imaging informatics. SIIM provides training and education in imaging informatics with courses eligible for education credits that lead to becoming a Certified Imaging Informatics Professional (CIIP) through the American Board of Imaging Informatics(ABII). Complete details at http://siim.org/page/iip_ciip_career.
Views: 494 SIIM Education
Michael W. Mahoney, Director of the Foundations of Data Analysis (FODA) Institute, UC Berkeley Random Matrix Theory (RMT) is applied to analyze the weight matrices of Deep Neural Networks (DNNs), including both production quality, pre-trained models and smaller models trained from scratch. Empirical and theoretical results clearly indicate that the DNN training process itself implicitly implements a form of self-regularization, implicitly sculpting a more regularized energy or penalty landscape. In particular, the empirical spectral density (ESD) of DNN layer matrices displays signatures of traditionally-regularized statistical models, even in the absence of exogenously specifying traditional forms of explicit regularization. Building on relatively recent results in RMT, most notably its extension to Universality classes of Heavy-Tailed matrices, and applying them to these empirical results, we develop a theory to identify 5+1 Phases of Training, corresponding to increasing amounts of implicit self-regularization. For smaller and/or older DNNs, this implicit self-regularization is like traditional Tikhonov regularization, in that there appears to be a ``size scale'' separating signal from noise. For state-of-the-art DNNs, however, we identify a novel form of heavy-tailed self-regularization, similar to the self-organization seen in the statistical physics of disordered systems. This implicit self-regularization can depend strongly on the many knobs of the training process. In particular, by exploiting the generalization gap phenomena, we demonstrate that we can cause a small model to exhibit all 5+1 phases of training simply by changing the batch size. This demonstrates that---all else being equal---DNN optimization with larger batch sizes leads to less-well implicitly-regularized models, and it provides an explanation for the generalization gap phenomena. Joint work with Charles Martin of Calculation Consulting, Inc. Bio: https://www.stat.berkeley.edu/~mmahoney/ Michael W. Mahoney is at the UCB in the Department of Statistics and at the International Computer Science Institute (ICSI). He works on algorithmic and statistical aspects of modern large-scale data analysis. Much of his recent research has focused on large-scale machine learning, including randomized matrix algorithms and randomized numerical linear algebra, geometric network analysis tools for structure extraction in large informatics graphs, scalable implicit regularization methods, and applications in genetics, astronomy, medical imaging, social network analysis, and internet data analysis. He received him PhD from Yale University with a dissertation in computational statistical mechanics. He has worked and taught at Yale University in the Math department, Yahoo Research, and Stanford University in the Math department. Among other things, he is on the national advisory committee of the Statistical and Applied Mathematical Sciences Institute (SAMSI), He was on the National Research Council's Committee on the Analysis of Massive Data. He co-organized the Simons Institute's fall 2013 program on the Theoretical Foundations of Big Data Analysis, and he runs the biennial MMDS Workshops on Algorithms for Modern Massive Data Sets. He is currently the lead PI for the NSF/TRIPODS-funded FODA (Foundations of Data Analysis) Institute at UC Berkeley. He holds several patents for work done at Yahoo Research and as Lead Data Scientist for Vieu Labs, Inc., a startup re-imagining consumer video for billions of users. More information is available at https://www.stat.berkeley.edu/~mmahoney/ Long version of the paper (upon which the talk is based): https://arxiv.org/abs/1810.01075 https://www.meetup.com/SF-Bay-ACM/events/255894048/ http://www.meetup.com/SF-Bay-ACM/ http://www.sfbayacm.org/
Views: 238 San Francisco Bay ACM
Complete News At: https://www.newsvisionindia.tv/2019/01/ZH-Foundation-Talent-Search-Exam-2019-Organized.html Also Read: इस खुलासे से मचा हड़कंप, नेताओं और अधिकारियों के घर भेजी जाती थीं सुधारगृह की लड़कियां https://goo.gl/KWQiA4 तुरंत जाने, आपके आधार कार्ड का कहां-कहां हुआ इस्तेमाल https://goo.gl/ob6ARJ मेरा बलात्कार या हत्या हो सकती है: दीपिका सिंह राजावत, असीफा की वकील https://goo.gl/HUNDvt हनिप्रीत की सेंट्रल जेल में रईसी, हर रोज बदलती है डिजायनर कपड़े https://goo.gl/3veAeH माँ ही मजूबर करती थी पोर्न देखने, अजीबोगरीब आपबीती सुनाई नाबालिग लड़की ने https://goo.gl/a5PGZ1 सिंधियों को बताया पाकिस्तानी, छग सरकार मौन, कभी मोदी ने भी थी तारीफ सिंधियो की https://goo.gl/kRuvqg Please Subscribe Us At: Youtube: http://youtube.com/c/NewsVisionIndia Google Plus: https://plus.google.com/u/0/ FaceBook: https://www.facebook.com/newsvisionindia/ WhatsApp: +91 9589333311 Twitter: https://twitter.com/newsvision111 LinkedIn: www.linkedin.com/in/News-Vision-India For Donation Bank Details Account Name: News vision Account No: 6291002100000184 Bank Name: Punjab national bank IFS code: PUNB0629100 Via Google Pay Number: +91 9589333311 #ZHFoundationTalentSearchExam2019OrganizedWithHugeSuccess, #NewsVisionIndia, #IndiaNewsHindiSamachar,
Views: 176 News Vision India
Presented By: Anastas Popratiloff, MD, PhD - Lead Research Scientist GW Nanofabrication and Imaging Center and Professor of Anatomy and Cell Biology GW School of Medicine and Health Sciences Speaker Biography: The prime aspect of my work is to serve as a director of the George Washington (GW) University's Nanofabrication and Imaging Center (NIC). In this role I incorporate research instrumentation and work-flow based approaches aiming to facilitate research discovery process. Another considerable part of my effort focuses on neuroscience research exploring animal models of diseases. These two lines of responsibility are connected via microscopic imaging, which as a final outcome aims to reverse engineer the abnormal brain and lead to a better understanding of the structural foundations of neuro-developmental disorders. I obtained a M.D. in 1991 from the Medical University of Sofia and a doctorate in medical sciences from the University of Cologne in 2000. My passion to study neuronal structure and connectivity with electron and light microscopy was developed as a medical student and lead me to pursue academic career. Webinar: Acceleration of Neuroscience Research Discovery by Incorporation of Large Area/Volume Microscopic Data Webinar Abstract: Modern microscopes are becoming increasingly complex instruments enabling registration of image sets far beyond a single field of view. This is being achieved by integration of sophisticated scanning stages, capable of moving the field of view in precise synchrony with acquisition, providing reliable meta data encoding time, space and multiple imaging modalities. As a result, increasingly complex multi-dimensional microscopic data sets are being generated and analyzed. For all these reasons, multifaceted workflows are required from sample preparation, through imaging to structuring and analyses of the image data. Studies of neuronal networks are a prime example of where complex image data facilitates our understanding of structural organization of neuronal circuits. The needs of large image data sets is amplified by the fact that in the CNS, elements of a single neuron span very large volumes, which ideally should be included in the image sets at appropriate resolution. It is also important to identify the neuropathological process at its emergence, where only rare events, representing foci of the nascent pathological process are present in otherwise normal brain tissue. In this webinar, we provide several examples of how modern light, electron and correlative microscopy facilitated our efforts to identify the underlying pathology associated with feeding and swallowing deficits present in a mouse model of 22q11D.2DS (LgDel). The webinar will highlight high-resolution confocal imaging approaches of a whole cleared embryos and reconstructions and analysis of single neurons. The values of large area light-to-SEM correlative workflows will be presented, followed by elastic backscatter imaging to produce TEM-like image sets both for generation of large area/high-resolution or 3D data sets for structural cellular analyses. Finally, the talk will underscore the value of postembedding immunogold detection of GABA-neurotransmitter using SEM backscatter imaging. Learning Objectives: -High-resolution confocal imaging approaches for whole cleared embryos and reconstructions and analysis of single neurons. -Large area light-to-SEM correlative workflows and elastic backscatter imaging for generation of large area/high-resolution or -3D data sets for structural cellular analyses. -Postembedding immunogold detection of GABA-neurotransmitter using SEM backscatter imaging. Earn PACE Credits: 1. Make sure you’re a registered member of LabRoots (https://www.labroots.com/ms/webinar/acceleration-neuroscience-research-discovery) 2. Watch the webinar on YouTube or on the LabRoots Website (https://www.labroots.com/ms/webinar/acceleration-neuroscience-research-discovery) 3. Click Here to get your PACE credits (Expiration date – 2 years webinar date): https://www.labroots.com/credit/pace-credits/3199/third-party LabRoots on Social: Facebook: https://www.facebook.com/LabRootsInc Twitter: https://twitter.com/LabRoots LinkedIn: https://www.linkedin.com/company/labroots Instagram: https://www.instagram.com/labrootsinc Pinterest: https://www.pinterest.com/labroots/ SnapChat: labroots_inc
Views: 32 LabRoots
The BSc/MSci in Applied Medical Sciences degree aims to develop a new breed of scientist, equipped with a strong knowledge of clinical medicine and the ability to develop scientific ideas into clinical concepts. Applied Medical Sciences degrees differs from most biomedical science degrees in that students develop a very strong understanding of the foundations of medicine, with an emphasis on fusing science with medicine. The BSc degree is angled towards the development of an appreciation of how science helps us to understand and treat various diseases. This applied science degree will enable you to become a highly skilled scientist who can make medicine work for patients. Alternatively, you might like to use your knowledge to find a career in research. You will also be able to adapt your skills to a variety of other professions where an understanding of science and medicine are crucial. We expect all our graduates to be capable of working in any of the biomedical sciences that they choose to pursue. We envisage that our graduates will play key roles in clinical trials, biomedical research, nanotechnology, drug design, the pharmaceutical industry, the regenerative repair industry and postgraduate research. For more information and to apply, please visit www.ucl.ac.uk/prospective-students/undergraduate/degrees/applied-medical-sciences-bsc/
Views: 607 UCL Faculty of Medical Sciences
Ross University School of Medicine offers two curriculum tracks during the Foundations of Medicine portion of the medical education program. These curriculum options are designed to cultivate student success further and empower you to advance through the basic sciences at a pace that aligns with your personal study needs. Learn more about our two curriculum tracks: http://medical.rossu.edu/medical-school/academics/two-curriculum-options.cfm Important information about the educational debt, earnings, and completion rates of students who attended this program can be found at http://medical.rossu.edu/medical-school/gainful-employment.htm
Views: 4927 Ross University School of Medicine
Implications in Medical Imaging of the New ICRP Thresholds for Tissue Reactions Eliseo Vaño, ICRP C3 Chair, Complutense University, Spain
Views: 40 ICRP
Biomedical Physics is an interdisciplinary graduate program in the David Geffen School of Medicine at UCLA. Faculty and students in the program are involved in Biomedical Research in Radiological Imaging and Therapy that operates at the intersection of traditional disciplines.
Views: 1009 UCLARadiology
You are NOT your MRI. You are NOT your diagnosis and you are NOT just another statistic. You are YOU. Here’s the troubling truth behind unreliable diagnostic imaging, the quick fix surgery business and the big compounding problem which is today’s mainstream medical industry. Full article here: https://drjohnrusin.com/you-are-not-your-fcking-mri/ I'm exceptionally fortunate to be working with clients and athletes every single day on my Foundations Program. They are stepping up, and proving their MRI's wrong while rebuilding their bodies WITHOUT surgery. If you need a restart to intelligent training, I cannot recommend this program and resource enough. https://drjohnrusin.com/foundations/
Views: 350 John Rusin
Follow Max during his MEG Scan at the CHOP Lurie Family Foundations MEG Imaging Lab. For more: Resources that highlight our research and MEG technology at CHOP: http://www.research.chop.edu/programs/car/our_team/details/?cat=1&id=5 http://www.chop.edu/treatments/magnetoencephalography-meg-scan#.VVtuX7lVhBc http://www.chop.edu/news/brain-imaging-links-language-delay-chromosome-deletion-children-neurological-disorders#.VVtu-rlVhBc http://www.cnet.com/news/diagnosing-autism-with-meg-imaging/ https://www.youtube.com/watch?v=UtmSNMurmX4 http://usa.healthcare.siemens.com/news-and-events/autism-research