Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis

Medical Ultrasound, and Preterm, Perinatal and Paediatric Image Analysis
Author: Yipeng Hu
Publisher: Springer Nature
Total Pages: 345
Release: 2020-10-01
Genre: Computers
ISBN: 3030603342

This book constitutes the proceedings of the First International Workshop on Advances in Simplifying Medical UltraSound, ASMUS 2020, and the 5th International Workshop on Perinatal, Preterm and Paediatric Image Analysis, PIPPI 2020, held in conjunction with MICCAI 2020, the 23rd International Conference on Medical Image Computing and Computer-Assisted Intervention. The conference was planned to take place in Lima, Peru, but changed to an online event due to the Coronavirus pandemic. For ASMUS 2020, 19 contributions were accepted from 26 submissions; the 14 contributions from the PIPPI workshop were carefully reviewed and selected from 21 submissions. The papers were organized in topical sections named: diagnosis and measurement; segmentation, captioning and enhancement; localisation and guidance; robotics and skill assessment, and PIPPI 2020.

Artificial Intelligence in Medical Imaging

Artificial Intelligence in Medical Imaging
Author: Erik R. Ranschaert
Publisher: Springer
Total Pages: 369
Release: 2019-01-29
Genre: Medical
ISBN: 3319948784

This book provides a thorough overview of the ongoing evolution in the application of artificial intelligence (AI) within healthcare and radiology, enabling readers to gain a deeper insight into the technological background of AI and the impacts of new and emerging technologies on medical imaging. After an introduction on game changers in radiology, such as deep learning technology, the technological evolution of AI in computing science and medical image computing is described, with explanation of basic principles and the types and subtypes of AI. Subsequent sections address the use of imaging biomarkers, the development and validation of AI applications, and various aspects and issues relating to the growing role of big data in radiology. Diverse real-life clinical applications of AI are then outlined for different body parts, demonstrating their ability to add value to daily radiology practices. The concluding section focuses on the impact of AI on radiology and the implications for radiologists, for example with respect to training. Written by radiologists and IT professionals, the book will be of high value for radiologists, medical/clinical physicists, IT specialists, and imaging informatics professionals.

Fundamental and Advanced Fetal Imaging

Fundamental and Advanced Fetal Imaging
Author: Beth Kline-Fath
Publisher: Lippincott Williams & Wilkins
Total Pages: 2503
Release: 2014-09-09
Genre: Medical
ISBN: 1469883570

Effectively evaluate obstetric patients with Fundamental and Advanced Fetal Imaging: Ultrasound and MRI! Written by an impressive roster of leading fetal radiologists and maternal-fetal medicine specialists, with additional input from cardiologists, geneticists, and Doppler specialists, this state-of-the-art reference explores how to obtain the maximum information from fetal ultrasound and magnetic resonance imaging, so you can rule out pathologies with confidence – or identify them early enough to initiate the most appropriate interventions.

Medical Image Understanding and Analysis

Medical Image Understanding and Analysis
Author: Bartłomiej W. Papież
Publisher: Springer
Total Pages: 0
Release: 2020-07-08
Genre: Computers
ISBN: 9783030527907

This book constitutes the refereed proceedings of the 24th Conference on Medical Image Understanding and Analysis, MIUA 2020, held in July 2020. Due to COVID-19 pandemic the conference was held virtually. The 29 full papers and 5 short papers presented were carefully reviewed and selected from 70 submissions. They were organized according to following topical sections: ​image segmentation; image registration, reconstruction and enhancement; radiomics, predictive models, and quantitative imaging biomarkers; ocular imaging analysis; biomedical simulation and modelling.

Deep Learning for Computer Vision

Deep Learning for Computer Vision
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 564
Release: 2019-04-04
Genre: Computers
ISBN:

Step-by-step tutorials on deep learning neural networks for computer vision in python with Keras.

Statistical Methods for Machine Learning

Statistical Methods for Machine Learning
Author: Jason Brownlee
Publisher: Machine Learning Mastery
Total Pages: 291
Release: 2018-05-30
Genre: Computers
ISBN:

Statistics is a pillar of machine learning. You cannot develop a deep understanding and application of machine learning without it. Cut through the equations, Greek letters, and confusion, and discover the topics in statistics that you need to know. Using clear explanations, standard Python libraries, and step-by-step tutorial lessons, you will discover the importance of statistical methods to machine learning, summary stats, hypothesis testing, nonparametric stats, resampling methods, and much more.

Deep Medicine

Deep Medicine
Author: Eric Topol
Publisher: Basic Books
Total Pages: 373
Release: 2019-03-12
Genre: Health & Fitness
ISBN: 1541644646

A Science Friday pick for book of the year, 2019 One of America's top doctors reveals how AI will empower physicians and revolutionize patient care Medicine has become inhuman, to disastrous effect. The doctor-patient relationship--the heart of medicine--is broken: doctors are too distracted and overwhelmed to truly connect with their patients, and medical errors and misdiagnoses abound. In Deep Medicine, leading physician Eric Topol reveals how artificial intelligence can help. AI has the potential to transform everything doctors do, from notetaking and medical scans to diagnosis and treatment, greatly cutting down the cost of medicine and reducing human mortality. By freeing physicians from the tasks that interfere with human connection, AI will create space for the real healing that takes place between a doctor who can listen and a patient who needs to be heard. Innovative, provocative, and hopeful, Deep Medicine shows us how the awesome power of AI can make medicine better, for all the humans involved.

Machine Learning in Medical Imaging

Machine Learning in Medical Imaging
Author: Guorong Wu
Publisher: Springer
Total Pages: 271
Release: 2013-09-18
Genre: Computers
ISBN: 3319022679

This book constitutes the refereed proceedings of the 4th International Workshop on Machine Learning in Medical Imaging, MLMI 2013, held in conjunction with the International Conference on Medical Image Computing and Computer Assisted Intervention, MICCAI 2013, in Nagoya, Japan, in September 2013. The 32 contributions included in this volume were carefully reviewed and selected from 57 submissions. They focus on major trends and challenges in the area of machine learning in medical imaging and aim to identify new cutting-edge techniques and their use in medical imaging.

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning

Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning
Author: Rani, Geeta
Publisher: IGI Global
Total Pages: 586
Release: 2020-10-16
Genre: Medical
ISBN: 1799827437

By applying data analytics techniques and machine learning algorithms to predict disease, medical practitioners can more accurately diagnose and treat patients. However, researchers face problems in identifying suitable algorithms for pre-processing, transformations, and the integration of clinical data in a single module, as well as seeking different ways to build and evaluate models. The Handbook of Research on Disease Prediction Through Data Analytics and Machine Learning is a pivotal reference source that explores the application of algorithms to making disease predictions through the identification of symptoms and information retrieval from images such as MRIs, ECGs, EEGs, etc. Highlighting a wide range of topics including clinical decision support systems, biomedical image analysis, and prediction models, this book is ideally designed for clinicians, physicians, programmers, computer engineers, IT specialists, data analysts, hospital administrators, researchers, academicians, and graduate and post-graduate students.