Intelligent Vision in Healthcare -- Diagnosis of Covid-19 in X-ray and CT Images Using Online Clustering Framework -- Unsupervised Deep Learning Approach for the Identification of Intracranial haemorrhage in CT images using PCA-Net and K-Means algorithm -- Automatic segmentation of optic cup and optic disc using MultiResUnet for Glaucoma classification from fundus image -- A Framework to Classify the Calcification Region from USG Images of Thyroid Nodules -- Predicting Heart Disease with Multiple Classifiers.

This book focuses on various aspects of computer vision applications in the field of healthcare. It covers new tools and technologies in some of the important areas of medical science like histopathological image analysis, cancer taxonomy, use of deep learning architecture dental care, and many more. Furthermore, this book reviews and discusses the use of intelligent learning-based algorithms for increasing the precision in medical domain. The book discusses different computer vision algorithms which are useful in various industries and day-to-day life. It also highlights many challenges faced by research community, like view point variations, scale variations, illumination variations, multi-modalities, and noise.