Automated content based methods for retrieval of similar images serve as efficient
management tools for handling large amounts of data. In medical imaging, they can also be …

A computer assisted system for automatic retrieval of medical images with similar image
contents can serve as an efficient management tool for handling and mining large scale …

The collections of various digital image databases have significantly grown and many users
have recognized that finding and recovering important images from large collections is a …

Image retrieval is a common technique to find similar images in a dataset given a query
image. Given such an image, this can for example be used to find images showing similar …

Over the past decades, medical image analytics was greatly facilitated by the explosion of
digital imaging techniques, where huge amounts of medical images were produced with …

Closing the semantic gap in medical image analysis is critical. Access to large-scale
datasets might help to narrow the gap. However, large and balanced datasets may not …

A content-based image retrieval (CBIR) framework for diverse collection of medical images
of different imaging modalities, anatomic regions with different orientations and biological …

Content Based Medical Image Retrieval (CBMIR) is a technique that search relevant images
in large repositories according to the content of the query image which is based on selected …

This chapter proposes a deep learning system for medical image retrieval based on content
by training a profound convolutionary neural network for the purpose of classification. The …

Learning and extracting representative features along with similarity measurements in high
dimensional feature spaces is a critical task. Moreover, the problem of how to bridge the …