Nilanjan Ray

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We propose a cell detection and tracking solution using image-level sets computed via threshold decomposition. In contrast to existing methods where manual initialization is required to track individual cells, the proposed approach can automatically identify and track multiple cells by exploiting the shape and intensity characteristics of the cells. The(More)
Inhaled hyperpolarized helium-3 (3He) gas is a new magnetic resonance (MR) contrast agent that is being used to study lung functionality. To evaluate the total lung ventilation from the hyperpolarized 3He MR images, it is necessary to segment the lung cavities. This is difficult to accomplish using only the hyperpolarized 3He MR images, so traditional(More)
The problem of identifying and counting rolling leukocytes within intravital microscopy is of both theoretical and practical interest. Currently, methods exist for tracking rolling leukocytes in vivo, but these methods rely on manual detection of the cells. In this paper we propose a technique for accurately detecting rolling leukocytes based on Bayesian(More)
Inflammatory disease is initiated by leukocytes (white blood cells) rolling along the inner surface lining of small blood vessels called postcapillary venules. Studying the number and velocity of rolling leukocytes is essential to understanding and successfully treating inflammatory diseases. Potential inhibitors of leukocyte recruitment can be screened by(More)
Recording rolling leukocyte velocities from intravital microscopic video imagery is a critical task in inflammation research and drug validation. Since manual tracking is excessively time consuming, an automated method is desired. This paper illustrates an active contour based automated tracking method, where we propose a novel external force to guide the(More)
A significant medical informatics task is indexing patient databases according to size, location, and other characteristics of brain tumors and edemas, possibly based on magnetic resonance (MR) imagery. This requires segmenting tumors and edemas within images from different MR modalities. To date, automated brain tumor or edema segmentation from MR(More)
Biomedical Image Analysis: Tracking #1598290185, 9781598290189 #Morgan & Claypool Publishers, 2006 #2006 #Scott T. Acton, Nilanjan Ray #144 pages Biomedical Image Analysis: Tracking addresses methods for extracting image information from biological/medical images for use in tracking biological targets. Here, and in the forthcoming companion Biomedical Image(More)
Tumor/abnormality segmentation from magnetic resonance imagery (MRI) can play a significant role in cancer research and clinical practice. Although accurate tumor segmentation by radiologists is ideal, it is extremely tedious. Experience shows that for MRI database indexing purposes approximate segmentations can be adequate. In this paper, we propose a(More)
INTRODUCTION Our objectives were to assess reliability, validity, and time efficiency of semiautomatic segmentation using Segura software of the nasal and pharyngeal airways, against manual segmentation with point-based analysis with color mapping. METHODS Pharyngeal and nasal airways from 10 cone-beam computed tomography image sets were segmented(More)
In this paper we propose a locally adaptive image threshold technique via variational energy minimization. The novelty of the proposed method is that from an image it automatically computes the weights on the data fidelity and the regularization terms in the energy functional, unlike many other previously proposed variational formulations that require(More)