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In this paper, we propose a new approach for color textured image segmentation. It is a two stage technique, where in the first stage, textural features using gray level co-occurrence matrix (GLCM) are computed for regions of interest (ROI)considered for each class. ROI act as ground truths for the classes. Ohta model (I1, I2, I3) is the colour model used for segmentation. Mean at inter pixel distance...
Acute lymphoblastic leukemia (ALL) are a group of hematological neoplasia of childhood which is characterized by a large number of lymphoid blasts in the blood stream. ALL makes around 80% of childhood leukemia and it mostly occur in the age group of 3-7. The nonspecific nature of the signs and symptoms of ALL often leads to wrong diagnosis. Diagnostic confusion is also posed due to imitation of similar...
Acute lymphoblastic leukemia (ALL) is the most common hematological neoplasia of childhood and is characterized by uncontrolled growth of leukemic cells in bone marrow, lymphoid organs etc. The nonspecific nature of the signs and symptoms of ALL often leads to wrong diagnosis. Diagnostic confusion is also posed due to imitation of similar signs by other disorders. Careful microscopic examination of...
In this paper, the problem of medical image segmentation is addressed in an unsupervised framework. We propose a novel method considering the hidden Markov random field model (HMRF) to model the image class labels, which takes into account the mutual influences of neighboring sites formulated on the basis of fuzzy clustering principle. The model parameters, number of class labels and the image labels...
This paper examines hybrid genetic algorithm and Gaussian Markov random field model based method for unsupervised segmentation of multi-spectral textured images. It also evaluates the popular unsupervised image segmentation approaches, Genetic algorithm (GA) based clustering and simple Gaussian Markov random field (GMRF) model with the hybrid GA-GMRF method for high spatial resolution textured imagery...
Acute lymphoblastic leukemia (ALL) is an serious hematological neoplasia of childhood which is characterized by abnormal growth and development of immature white blood cells (lymphoblasts). ALL makes around 80% of childhood leukemia and it mostly occur in the age group of 3-7. The nonspecific nature of the signs and symptoms of ALL often leads to wrong diagnosis. Diagnostic confusion is also posed...
Image fusion refers to the process of combining two or more images into one composite image, which integrates the information contained within the individual images. In this paper, we have proposed a new image fusion scheme for remotely sensed images to fuse multispectral (MS) and panchromatic (Pan) images. The existing standard Intensity Hue Saturation (IHS) method as well as "a trous"...
In this paper we propose a novel algorithm for object tracking from Video images based on segmentation and Kernel based procedure. Many Kernel based object tracking algorithms have been developed during last few years. The computational complexity becomes very high in those kernel based techniques. In our proposed method the target localization problem is minimized using segmentation technique, instead...
A cute lymphocytic leukemia (ALL) is a malignant disease characterized by the accumulation of lymphoblast in the bone marrow. An improved scheme for ALL detection in blood microscopic images is presented here. In this study features i.e. hausdorff dimension and contour signature are employed to classify a lymphocytic cell in the blood image into normal lymphocyte or lymphoblast (blasts). In addition...
In this paper we propose a novel algorithm for object tracking from Video images based on segmentation and Kernel based procedure. Many Kernel based object tracking algorithms have been developed during last few years. The computational complexity becomes very high in those kernel based techniques. In our proposed method the target localization problem is minimized using segmentation technique, instead...
In recent times, telemedicine has become an essential and integral part of e-healthcare. Telemedicine helps a patient to receive health care services from distant location. Under the diverse scenario of health care services, it is often required that different telemedicine systems should interoperate with each other. However, syntactic and/or semantic mismatch in data and service often restrict the...
In this paper we propose a novel method for object tracking in video images. The method is based on image segmentation and pattern matching. All moving and still objects in video images can be detected accurately with the help of efficient image segmentation techniques. We propose a hybrid algorithm for image segmentation using the notion of Particle Swarm Optimization (PSO) and Fuzzy-C-Means (FCM)...
In modern health care, use of Web based EHR (electronic health record) system has increased remarkably because of its world-wide accessibility and the facility of the collaborative work among multiple users. Major drawbacks of such centralized Web based system are link failure and low or no fault tolerance. In an unreliable network, it is very commonplace that service is unavailable due to connection...
In this paper, image segmentation of brain magnetic resonance (MR) image is addressed in an unsupervised framework. We propose a novel method considering the hidden Markov random field model (HMRF) to model the image class labels, which takes into account the mutual influences of neighbouring sites formulated on the basis of fuzzy clustering principle. By introducing the effective means to incorporate...
HIV infection is one of the major health problems in today's world, especially in a developing country like India. The impact of HIV on the pediatric population is no less dreadful. Pediatric HIV is a subset of HIV which requires special attention. Efficient information management is one of the key issues in pediatric HIV treatment. Electronic health record (EHR) plays an important role in patient...
We propose two new schemes for segmentation of images with uneven lighting conditions. These are based on adaptive window selection. The first one is a window merging method based on Lorentz information measure (LIM) but the second one is a window growing method using the notion of entropy. We propose two new window merging criterion where the window merging is carried out based on linear combination...
In this paper, we created a generalized framework for the automated placement and routing of analog test structures. We exploited the concept of terminal properties when placing and routing the test structures and generated a library of place and routing strategies for different architectures. This new approach significantly reduces layout time, maximizes the reuse of place and route routines, and...
In this paper, a new notion of image segmentation using Markov random field (MRF) model learning feature is addressed. The segmentation problem is formulated as pixel labeling problem in a supervised framework. MRF model is employed to model the class labels. This model learns a given training image derived from a class of images. The model having learnt is validated for other images of the same class...
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