optical coherence tomography (oct) is a powerful imaging modality used to image various aspects of biological tissues, such as structural information, blood flow, elastic parameters, change of polarization states, and molecular content [1]. in contrast to oct technology development which has been a field of active research since 1991, oct image segmentation has only been more fully explored dur...

We present an integrated methodology for detecting, segmenting and classifying breast masses from mammograms with minimal user intervention. This is a long standing problem due to low signal-to-noise ratio in the visualisation of breast masses, combined with their large variability in terms of shape, size, appearance and location. We break the problem down into three stages: mass detection, mas...

Introduction: Lung cancer is one of the most common causes of cancer-related deaths worldwide. Nowadays PET/CT plays an essential role in radiotherapy planning specially for lung tumors as it provides anatomical and functional information simultaneously that is effective in accurate tumor delineation. The optimal segmentation method has not been introduced yet, however several ...

In this paper we propose a supervised method for the segmentation of masses in mammographic images. The algorithm starts with a selected pixel inside the mass, which has been manually selected by an expert radiologist. Based on the active region approach, an energy function is defined which integrates texture, contour and shape information. Then, pixels are aggregated or eliminated to the regio...

A tumor is a mass of tissue that grows out of control of the normal forces that regulates growth. The detection of tumor and its quantitative analysis allows obtaining useful key indicators of disease progression at early stages. Tumor detection using segmentation embraces a significant position in the region of image processing. It becomes more and more significant while dealing with multimoda...

Accurate liver segmentation is essential for surgery planning and diagnosis of liver abnormality with algorithms. We propose and validate a multi-atlas segmentation approach with local decision fusion for fast automated liver (with/without abnormality) segmentation on computational tomography angiography (CTA). Thirty-five patients were enrolled in this study. A co-registered segmented CTA atla...

Background and Objectives: Identification of surgical instruments in laparoscopic video images has several biomedical applications. While several methods have been proposed for accurate detection of surgical instruments, the accuracy of these methods is still challenged high complexity of the laparoscopic video images. This paper introduces a Surgical Instrument Detection Framework (SIDF) for a...

in today's competitiveenvironment, customers are the most important asset to any company. therefore,in order to retain customers, it is essential to understandtheirbehaviour for developing effective strategies. one of the most commonmethods for customer analysis is market segmentation that helps companies todevelop marketing technique by dividing market into several smaller homogeneousgrou...

Introduction: Nowadays virtual colonoscopy has become a reliable and efficient method of detecting primary stages of colon cancer such as polyp detection. One of the most important and crucial stages of virtual colonoscopy is colon segmentation because an incorrect segmentation may lead to a misdiagnosis.  Materials and Methods: In this work, a hybrid method based on Geometric Deformable Models...