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Ultrasound has shown a great potential for serving as an outcome measure for localized scleroderma. High spatial resolution of ultrasound will aid to evaluate Echogenicity, Vascularity index and tissue thickness of localized scleroderma. Echogenicity is higher when the ultrasound waves reflected are lesser in value from any particular body organ. Vascularity index can be defined as the differences...
In this paper, a new algorithm is proposed to segment medical images to extract the contour of the objects. First, do edge segmentation to the image region with Prewitt operator. And then use Hough transformation to detect the incontinuous points in curve and link the edges. An accurate edge of the organ or tissue of human can be extracted through this method. Based on this, more information can be...
Image segmentation is an important branch of computer vision. Its aim is to extract meaningful lying in objects images, either by dividing images into contiguous semantic regions, or by extracting one or several objects more specific in images, such as medical structures. In general, image segmentation task is very difficult to achieve it since natural images are diverse, complex and the way we perceive...
Glaucoma is one of the main causes of blindness worldwide. Segmentation of vascular system and optic disc is an important step in the development of an automatic retinal screening system. In this paper we present an unsupervised method for the optic disc segmentation. The main obstruction in the optic disc segmentation process is the presence of blood vessels breaking the continuity of the object...
With the increased use of digital images in numerous fields, especially sensitive ones like medicine and military where confidentiality is extremely important, their encryption has become mandatory. This paper depicts our proposed digital image encryption technique which employs two types of non-linear pixel transformation and the traditional Hill cipher which is a Matrix Transformation (MT). While...
This paper present the results of applying dark stretching technique to enhance and segment the Plasmodium Falciparum based on thick blood smear images. Image enhancement is the process to improve the quality (clarity) of images for human viewing. Removing blurring and noise, increasing contrast, and revealing details are examples of enhancement operations. Reducing the noise and blurring and increasing...
Ultrasound imaging is a widely used and safe medical diagnostic technique, due to its noninvasive nature, low cost, real time imaging. However the usefulness of ultrasound imaging is degraded by the presence of signal depended noise known as speckle.. The speckle pattern depends on the structure of the image tissue and various imaging parameters. There are two main purposes for speckle reduction in...
In the field of medicine, storing images in a secure way has become a challenge. In order to face this challenge of security, we propose an algorithm based on visual cryptography for black and white medical images. Here, we bring out a new approach to visual cryptography. The main advantage of this system is that there is no necessity for post processing of the image without which a good quality of...
Patient motion degrades image quality in medical imaging. Gating can reduce motion artifacts by using part of the acquired data, but can increase noise. Motion-compensated image reconstruction (MCIR) utilizes all collected data with motion information to reduce motion artifacts and noise. Interactions between Poisson log-likelihood and quadratic regularizers lead to nonuniform and anisotropic spatial...
A reliable and accurate method to measure the width of retinal blood vessel in fundus photography is proposed in this paper. Our approach is based on a graph-theoretic algorithm. The two boundaries of the same blood vessel are segmented simultaneously by converting the two-boundary segmentation problem into a two-slice, three-dimension surface segmentation problem, which is further converted into...
A novel interactive segmentation method based on distance metric learning is proposed for segmentation of tumors in CT and MRI images. Firstly, the moments of the gray-level histogram are extracted as the image features for segmentation. Then, Neighborhood Components Analysis is employed to learn a task-specific distance metric in the feature space using the interactive inputs. The probability of...
The Local Positioning System consists of a methodology proposed for monitoring swimmers training by means of processing real time images of the pool from outside. To evaluate the proposed technique experiments have been done using static and dynamic markers, aiming to simulate a swimmer, in a simulated pool environment. Considering the image processing, the size of the smallest marker that could be...
Microcalcifications are present in a great number of malignant lesions, being considered as a significant sign of malignancy. However, they are detected in less than 50% of mammograms with carcinomas. Given this scenario, systems to highlight infra-clinic lesions, aiding the specialists to make diagnostics, have been studied. These Computer-aided diagnosis systems have been developed based on parameters...
A new method of reconstructing three-dimensional (3D) tubular structures from cone-beam projections is proposed in this paper. Minimal path method is applied to detect 2D tubular structures in the cone-beam projections. The extracted 2D information are fused to design a weight function over the 3D volume so that minimal path method can be applied again to extract centerlines of 3D tubular structures...
This paper presents an algorithm to classify pixels in uterine cervix images into two classes, namely normal and abnormal tissues, and simultaneously select relevant features, using group sparsity. Because of the large variations in image appearance due to changes of illumination, specular reflections and other visual noise, the two classes have a strong overlap in feature space, whether features...
This paper presents ongoing work towards creating a framework for the active segmentation and classification of cell assay images. In this paper we focus on the learning of a probabilistic boundary model followed by an extended segmentation method. The abilities are demonstrated on a variety of cell images. We conclude by outlining approaches for the active segmentation of cell images.
Retinal image analysis is currently a very vivid field in biomedical image analysis. One of the most challenging tasks is the reliable automatic detection of microaneurysms (MAs). Computer systems that aid the automatic detection of diabetic retinopathy (DR) greatly rely on MA detection. In this paper, we present a method to construct an MA score map, from which the final MAs can be extracted by simple...
Filamentary structures extraction in medical and biological images is a challenging problem. Muscular/Neural fibers, neurites and blood arteries are some examples. Their delineation is particularly problematic due to the lack of solid visual support that is also compromised by the presence of clutter and low signal to noise ratios. In this article, we propose a modular approach to curvilinear structures...
The ocular fundus image can provide information on pathological changes caused by local ocular diseases and early signs of certain systemic diseases, such as diabetes and hypertension. Automated analysis and interpretation of fundus images has become a necessary and important diagnostic procedure in ophthalmology. The extraction of blood vessels from retinal images is an important and challenging...
Segmentation of tree-like structure within medical imaging modalities, such as x-ray, MRI, ultrasound, etc., is an important step for analyzing branching patterns involved in many anatomic structures. However, images acquired using these different acquisition techniques frequently have features of poor contrast, blurring and noise, and therefore the segmentation result of traditional image segmentation...
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