Image analysis in the medical field aims to offer tools for the diagnosis and detection of life-
threatening illness. This study means to propose a novel content-based image retrieval …

This paper presents an information fusion method for the automatic classification and
retrieval of prostate histopathology whole-slide images (WSIs). The approach employs a …

The use of digital medical imaging systems in healthcare institutions has increased
significantly, and the large amounts of data in these systems have led to the conception of …

Modern neural networks achieve state-of-the-art results on land cover classification from
satellite imagery, as is the case for almost all vision tasks. One of the main challenges in this …

This research work explores the Content-Based Medical Image Retrieval system (CBMIR) to
categorization and retrieval of different types of common thoracic diseases such as …

Abstract Electronic Health Records (EHRs) provide vital contextual information to
radiologists and other physicians when making a diagnosis. Unfortunately, because a given …

The purpose of the present study is to evaluate whether an online reference system (ORS,
STATdx Elsevier, Amsterdam, Netherlands) impacts finding the histologically confirmed …

In recent years, deep learning has become a powerful tool for medical image analysis
mainly because of their ability to automatically extract more abstract features from large …

This article presents an ingestion procedure towards an interoperable repository called
ALPACS (Anonymized Local Picture Archiving and Communication System). ALPACS …

One of the main challenges in medical image retrieval is the increasing volume of image
data, which render it difficult for domain experts to find relevant information from large data …