Background CT findings of lung cancer and tuberculosis are sometimes similar, potentially
leading to misdiagnosis. This study aims to combine deep learning and content-based …

Today, much of the information is storing in images. To transfer information in the form of
images, image compression is required. Compressing images reduces the size of images …

Diabetics suffer from an eye condition called diabetic retinopathy (DR), which can lead to
vision loss. The main region affected is the blood vessels in the retina. A large proportion of …

Image content analysis plays a major role in image classification, retrieval, and indexing
together with object and scene recognition. Numerous image content descriptors are …

The increasing size of medical image repositories is due to the increasing number of digital
imaging data sources. Most of the image content descriptors proposed in the literature are …

Medical image retrieval (MIR) is a hard task owing to the varied patterns and structures in
the medical images. The feature descriptors have been used to describe the images in most …

This study presents a flexible directional filter bank (DFB) by tuning Hermite transform
parameters for content‐based medical image retrieval (CBMIR). Two imperative Hermite …

Retrieving required medical images from a huge amount of images is one of the most widely
used features in medical information systems, including medical imaging search engines …

A new feature descriptor called local bit-plane domain 3D oriented arbitrary and circular
shaped scanning pattern (LB-3D-OACSP) is proposed for biomedical image retrieval in this …

Biomedical image classification is an important task to generate classification maps for
deadly diseases like cancer, tumor, etc. In this paper, a novel technique for classification of …