▪ Abstract Image segmentation plays a crucial role in many medical-imaging applications, by
automating or facilitating the delineation of anatomical structures and other regions of …

The aim of this paper is to review existing approaches to the automatic detection and
segmentation of masses in mammographic images, highlighting the key-points and main …

Heterogeneity is a key feature of malignancy associated with adverse tumour biology.
Quantifying heterogeneity could provide a useful non-invasive imaging biomarker …

Texture analysis is widely performed in the current time as it is considered as an intimate
property of the surface. It is widely used in the field of image processing, remote sensing …

A computer-assisted diagnostic (CAD) method and appara tus are described for the
enhancement and detection of suspicious regions in digital X-ray images. with particular …

Texture analysis was applied to high‐resolution, contrast‐enhanced (CE) images of the
breast to provide a method of lesion discrimination. Significant differences were seen …

Human eye is one of the most sophisticated organ, with retina, pupil, iris cornea, lens and
optic nerve. Automatic retinal image analysis is emerging as an important screening tool for …

This proposal tempts to develop automated DR detection by analyzing the retinal
abnormalities like hard exudates, haemorrhages, Microaneurysm, and soft exudates. The …

Purpose To evaluate whether changes in magnetic resonance (MR) imaging heterogeneity
may aid assessment for pathologic complete response (pCR) to neoadjuvant chemotherapy …

This paper presents a method for automatic breast pectoral muscle segmentation in
mediolateral oblique mammograms using a Convolutional Neural Network (CNN) inspired …