Volume 2

1 - Coronary and
carotid artery calcium detection, its quantification, and grayscale
morphology-based risk stratification in multimodality big data: a review

2 - A cloud-based
smart LD measurement tool for stroke risk assessment during multicenter
clinical trials

3 -
Multiresolution-based Coronary Calcium Volume Measurement Techniques from
Intravascular Ultrasound Videos

4 - Deep Learning
Fully Convolution Network for Lumen Characterization in Diabetic Patients using
Carotid Ultrasound: A tool for Stroke Risk

5 - Deep Learning
Strategy for Accurate Carotid Intima-Media Thickness measurement: an Ultrasound
Study on Japanese Diabetic Cohort

6 - MEMS based
manufacturing technique of vascular bed

7 - Risk of
Coronary Artery Disease: Genetics and External Factors

8 - Wall
Quantification and Tissue Characterization of Coronary Artery

9 - Rheumatoid
Arthritis: Its link to Atherosclerosis Imaging and Cardiovascular Risk
Assessment using Machine Learning-based Tissue Characterization

10 -
Echolucency-based Phenotype in Carotid Atherosclerosis Disease for Risk
Stratification of Diabetes Patients

11 - Plaque
Tissue Morphology-based Stroke Risk Stratification using Carotid Ultrasound: A
Polling-based PCA Learning Paradigm

12 - Morphologic
TPA (mTPA) and Composite Risk Score for Moderate Carotid Atherosclerotic Plaque
is strongly associated with HbA1c in Diabetes Cohort imminently

Cardiovascular disease (CVD) is responsible for a third of all deaths in women and more than a half in men. With mortality increasing worldwide each year, many issues are being raised as to how best treat CVD. For medical practitioners and scientists, important questions are being asked such as, what diagnoses and interventional strategies can be used? Which imaging techniques give the most information? And how should coronary interventions be evaluated to make the best possible diagnoses for future patients?

Exploring these questions in detail, this book gives a complete overview of the most recent research on vascular and intravascular analysis, it discusses different scientific and clinical questions in detail, and considers the latest advances in clinical treatment and medical imaging automatic analysis. Compiled by experts in the field, a thorough investigation is given to current topics and problems relating to CVD, which will enable the scientific and medical communities to search for the most effective strategies for dealing with these diseases.

As one of the most prominent diseases in our society, CVD requires dedicated analysis and investigation in order to reduce the mortality rate worldwide. Scholars, biomedical engineers and medical practitioners will greatly benefit from the detailed information in this book as it will give a better understanding of the causes, diagnosis and treatment of CVD.

Petia Radeva is a senior researcher and full professor at the University of Barcelona, where she is also the head of the Computer Vision and Machine Learning Consolidated Research Group (CVUB), as well as the head of Medical Imaging Laboratory (MiLab) of Computer Vision Centre, Spain. Her research interests include the development of deep learning, computer vision and lifelogging, and their applications to healthcare. Radeva is an IAPR Fellow, and she has received Icrea Academia and the CIARP Aurora Pons Porrata awards.

Jasjit S Suri is an innovator, scientist, industrialist and an internationally known world leader in biomedical engineering, sciences and its management. He has written numerous publications and is currently the chairman of AtheroPoint, USA, dedicated in stroke and cardiovascular imaging. He is a recipient of Life Time Achievement Award by Marquis (2018) and a Fellow of the American Institute of Medical and Biological Engineering (2004).