Computer-aided diagnosis (CAD) provides a computerized diagnostic result as a “second opinion” to assist radiologists in the diagnosis of various diseases by use of medical images. CAD has become a practical clinical approach in diagnostic radiology, although, at present, primarily in the area of detection of breast cancer in mammograms. Currently, a large research effort has been devoted to th...

In today’s medicine, Computer-Aided Diagnosis Systems (CAD) are very used to improve the screening test accuracy of pulmonary nodules. Processing, classification, and detection techniques form basis CAD architecture. this work, we focus on classification step in a system where use Discrete Cosine Transform (DCT) along with Convolutional Neural Network (CNN) perform an efficient method for Combi...

Breast cancer is one of the most common cancers among women of the developing countries in the world, and it has also become a major cause of death [1, 2]. Treatment of breast cancer is effective only if it is detected at an early stage. Xray Mammography is the most effective technique used by radiologists in the screening and diagnosis of breast cancer in women but the mammographic images are ...

In this paper, we investigate breast ultrasound images (BUSI) performing (CAD) Computer Aided Diagnosis of cancer, thereby predicting the stage malignant tumor in through effective speckle filtering, contrast enhancement, feature extraction and fusion. This model trains BUSI dataset by Convolutional neural network (CNN) using NPR tool.

We have developed computer-aided diagnosis (CAD) schemes for the detection of lung nodules, interstitial lung diseases, interval changes, and asymmetric opacities, and also for the differential diagnosis of lung nodules and interstitial lung diseases on chest radiographs. Observer performance studies indicate clearly that radiologists' diagnostic accuracy was improved significantly when radiolo...

Segmentation is an important step in medical image analysis and classification for radiological evaluation or computer aided diagnosis. This paper presents the problem of inaccurate lung segmentation as observed in algorithms presented by researchers working in the area of medical image analysis. The different lung segmentation techniques have been tested using the dataset of 19 patients consis...

In this paper we describe a computer-aided diagnosis (CAD) system for automated detection of pulmonary nodules in computed-tomography (CT) images. After extracting the pulmonary parenchyma using a combination of image processing techniques, a region growing method is applied to detect nodules based on 3D geometric features. We applied the CAD system to CT scans collected in a screening program ...

The aim of this paper is to describe three emerging computer-aided diagnosis (CAD) systems induced by Japanese health care needs. CAD has been developing fast in the last two decades. The idea of using a computer to help in medical image diagnosis is not new. Some pioneer studies are dated back to the 1960s. In 1998, the first U.S. FDA (Food and Drug Administration) approved commercial CAD syst...

PURPOSE to explore the clinical value of 3.0T magnetic resonance (MR) imaging compared with computer-aided MR diagnosis (MR-CAD) in differential diagnosis of benign and malignant breast tumors. MATERIALS AND METHODS MRI method and MR-CAD method was used in the diagnosis of a total of 93 breast lesions of 78 patients, based on the morphological and time-intensity-curve (TIC) analysis. The accu...