In this paper, we proposed a method for classification of medical images captured by
different sensors (modalities) based on multi-scale wavelet representation using dictionary …

In this paper, we propose a new secure content based image retrieval (SCBIR) system
adapted to the cloud framework. This solution allows a physician to retrieve images of …

Diagnosis of breast cancer in mammograms is also for specialists a difficult and error-prone
task. A good opportunity to support radiologists in their decision is to find similar …

The present work proposes a Multi-Output Classification Autoencoder (MOC-AE) algorithm
to extract features from brain tumour images. The proposed algorithm is able to focus on …

In this work, Multi-trend structure descriptor is suggested for retrieving images from
heterogeneous medical image dataset. The multi-trend structure descriptors acquires …

Abstract Background and Objective Content based medical image retrieval (CBMIR)
systems enable fast diagnosis through quantitative assessment of the visual information and …

A large collection of medical images surrounds health care centers and hospitals. Medical
images produced by different modalities like magnetic resonance imaging (MRI), computed …

In this article, new feature descriptor local bit plane adjacent neighborhood dissimilarity
pattern (LBPANDP) is introduced for CT image retrieval. In the proposed method, the input …

Purpose: To explore the feasibility of discriminating pancreatic cancer from normal pancreas
using texture features of non-enhanced computed tomography (CT) images. Methods: 312 …

The ever-increasing number of produced radiology images in medical centers makes
storage, classification and retrieval of these images an important and vital issue in …