Abstract preview: We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precis ... more

Abstract preview: We consider the problem of accurately identifying cell boundaries and labeling individual cells in confocal microscopy images, specifically, 3D image stacks of cells with tagged cell membranes. Precis ... more

Abstract preview: Images and video play a major role in scientific discoveries. Significant new advances in imaging science over the past two decades have resulted in new devices and technologies that are able to probe ... more

Abstract preview: Logistical and financial limitations of underwater operations are inherent in marine science, including biodiversity observation. Imagery is a promising way to address these challenges, but the divers ... more

Abstract preview: Logistical and financial limitations of underwater operations are inherent in marine science, including biodiversity observation. Imagery is a promising way to address these challenges, but the divers ... more

Abstract preview: Motivation: In addition to being involved in retinal vascular growth, astrocytes play an important role in diseases and injuries, such as glaucomatous neuro-degeneration and retinal detachment. Studyi ... more

Abstract preview: Dendritic spines serve as key computational structures in brain plasticity. Much remains to be learned about their spatial and temporal distribution among neurons. Our aim in this study was to perform ... more

Abstract preview: MOTIVATION:Microscopy advances have enabled the acquisition of large-scale biological images that capture whole tissues in situ. This in turn has fostered the study of spatial relationships between ce ... more

Abstract preview: Few technologies are more widespread in modern biological laboratories than imaging. Recent advances in optical technologies and instrumentation are providing hitherto unimagined capabilities. Almost ... more

Abstract preview: Two new textural descriptor, named N Concentric Squares Resized (NCSR) and N Concentric Squares Resized (NCSH), have been proposed. These descriptors were used to classify 472 images of alive spermato ... more

Abstract preview: Camera networks provide opportunities for practical video surveillance and monitoring, but tracking people across the network presents many computational and modeling hurdles that researchers have yet ... more

Abstract preview: This paper addresses the novel and challenging problem of aligning camera views that are unsynchronized by low and/or variable frame rates using object trajectories. Unlike existing trajectory-based a ... more

Abstract preview: This paper proposes a context-aware object search and retrieval in a wide area distributed camera network. With the proliferation of smart cameras in urban networks, it is a challenge to process this ... more

Abstract preview: This paper proposes a distributed multi-camera tracking algorithm with interacting particle filters. We propose a novel algorithm for multi-view appearance modeling by sharing training samples between ... more

Abstract preview: This paper proposes a novel system to assist human image analysts to effectively browse and search for objects in a camera network. In contrast to the existing approaches that focus on finding global ... more

Abstract preview: We present a simple multiple view 3D model for object tracking and identification in camera networks. Our model is composed of 8 distinct views in the interval [0, 7*PI/4]. Each of the 8 parts describ ... more

Abstract preview: Resampling is an important signature of manipulated images. In this paper, we propose two methods to detect and localize image manipulations based on a combination of resampling features and deep lear ... more

Abstract preview: In this article, we explored orthogonal methods to analyze malware motivated by signal and image processing. Malware samples are represented as images or signals. Image and signal-based features are e ... more

Abstract preview: There is an alarming increase in the amount of malware that is generated today. Several studies have shown that most of these new malware are just variants of existing ones. In this research we focus ... more

Abstract preview: There is an alarming increase in the amount of malware that is generated today. However, several studies have shown that most of these new malware are just variants of existing ones. Fast detection of ... more

Abstract preview: In this work, we propose SigMal, a fast and precise malware detection framework based on signal processing techniques. SigMal is designed to operate with systems that process large amounts of binary s ... more

Abstract preview: AI techniques play an important role in automated malware classification. Several machine-learning methods have been applied to classify or cluster malware into families, based on different features d ... more

Abstract preview: We propose a simple yet effective method for visualizing and classifying malware using image processing techniques. Malware binaries are visualized as gray-scale images, with the observation that for ... more

Abstract preview: Each year, underwater remotely operated vehicles (ROVs) collect thousands of hours of video of unexplored ocean habitats revealing a plethora of information regarding biodiversity on Earth. However, f ... more

Abstract preview: We present a model that generates close-to-human gaze sequences for a given image in the free viewing task. The proposed approach leverages recent advances in image recognition using convolutional neu ... more

Abstract preview: When modeling geo-spatial data, it is critical to capture spatial correlations for achieving high accuracy. Spatial Auto-Regression (SAR) is a common tool used to model such data, where the spatial co ... more

Abstract preview: Object localization is an important computer vision problem with a variety of applications. The lack of large scale object-level annotations and the relative abundance of image-level labels makes a co ... more

Abstract preview: We present a real-time body orientation estimation in a micro-Unmanned Air Vehicle video stream. This work is part of a fully autonomous UAV system which can maneuver to face a single individual in ch ... more

Abstract preview: We investigate the problem of image classification within a supervised learning framework that exploits implicit mutual information in different visual features and their associated classifiers. & ... more

Abstract preview: Visual attention is a crucial indicator of the relative importance of objects in visual scenes to human viewers. In this paper, we propose an algorithm to extract objects which attract visual attentio ... more

Abstract preview: This research focuses on enhancing computer vision algorithms using eye tracking and visual saliency. Recent advances in eye tracking device technology have enabled large scale collection of eye track ... more

Abstract preview: Coastal marine ecosystems are highly productive and diverse, but biodiversity of underwater habitats is poorly described due to logistical and financial limitations of diving and submersible operation ... more

Abstract preview: Segmentation based tracing algorithms detect the extent and borders of an object in a given frame Iz by propagating results from frames I < z < Z. While application specific tracers have been fo ... more

Abstract preview: Wide-area wireless camera networks are being increasingly deployed in many urban scenarios. The large amount of data generated from these cameras pose significant information processing challenges. In ... more

Abstract preview: Classification and Detection of biological structures in Electron Micrographs (EM) is a relatively new large scale image analysis problem. The primary challenges are in characterizing diverse visual c ... more

Abstract preview: We address the problem of cell segmentation in confocal microscopy membrane volumes of the ascidian Ciona used in the study of morphogenesis. The primary challenges are non-uniform and patchy membrane ... more

Abstract preview: Humans have a remarkable ability to quickly discern regions containing text from other noisy regions in images. The primary contribution of this paper is to learn a model to mimic this behavior and ai ... more

Abstract preview: This work addresses the problem of optimally solving Markov Random Fields(MRFs) in which labels obey a certain topology constraint. Utilizing prior information, such as domain knowledge about the appe ... more

Abstract preview: In this research we propose a combined cell matching and image alignment method for tracking cells based on their nuclear locations in 3D fluorescent Confocal Laser Scanning Microscopy (CLSM) image se ... more

Abstract preview: We introduce a fast and efficient variational framework for Simultaneous Registration and Segmentation (SRS) applicable to a wide variety of image sequences. We demonstrate that a dense correspondence ... more

Abstract preview: Robust methods for segmentation and tracking are critical for quantitative biology. We give an overview of our recent work on graph based methods for various microscopy image analysis, including traci ... more

Abstract preview: Automatic interpretation of Transmission Electron Micrograph (TEM) volumes is central to advancing current understanding of neural circuitry. In the context of TEM image analysis, tracing 3D neuronal ... more

Abstract preview: State of the art biological imaging methods, such as confocal microscopy, create 3D volumes by sampling on a cartesian grid. This cartesian coordinate system is often not convenient for visualization ... more

Abstract preview: We present a model for the automated segmentation of cells from confocal microscopy volumes of biological samples. The segmentation task for these images is exceptionally challenging due to weak boun ... more

Abstract preview: In this paper we introduce novel regulariza tion techniques for level set segmentation that target specically the problem of multiphase segmentation. When the multiphase model is used to obtain a part ... more

Abstract preview: Alzheimer's disease is a major cause of dementia for which treatments remain unsatisfactory. Cyclin-dependent kinase 5 (CDK5) is a relevant kinase that has been hypothesized to contribute to the ... more

Abstract preview: A novel interactive segmentation framework comprising of a two stage s-t mincut is proposed. The framework has been designed keeping in mind the need to segment touching neuronal structures in Electro ... more

Abstract preview: Tracking of curvilinear structures is a task of fundamental importance in the quantitative analysis of biological structures such as neurons, blood vessels, retinal interconnects, microtubules, etc. T ... more

Abstract preview: We present a method for object tracking over time sequence imagery. The image plane is represented with a 4-connected planar graph where vertices are associated with pixels. On each image, the outer c ... more

Abstract preview: Simultaneous registration and segmentation (SRS) provides a powerful framework for tracking an object of interest in an image sequence. The state-of-the-art SRSbased tracking methods assume that the i ... more

Abstract preview: We introduce a robust image segmentation method based on a variational formulation using edge flow vectors. We demonstrate the non-conservative nature of this flow field, a feature that helps in a bet ... more

Abstract preview: Background: We present a biosegmentation benchmark that includes infrastructure, datasets with associated ground truth, and validation methods for biological image analysis. The primary motivation for ... more

Abstract preview: In this paper, we present an algorithm for occlusion boundary detection. The main contribution is a probabilistic detection framework defined on spatio-temporal lattices, which enables joint analysis ... more

Abstract preview: We introduce a dynamical model for simultaneous registration and segmentation in a variational framework for image sequences, where the dynamics is incorporated using a Bayesian formulation. A linear ... more

Abstract preview: In this paper we demonstrate the effectiveness of reference (or atlas)-based non-rigid registration to the segmentation of medical and biological imagery. In particular we introduce a segmentation fun ... more

Abstract preview: In many neurophysiological studies, understanding the neuronal circuitry of the brain requires detailed 3D models of the nerve cells and their synapses. Typically, researchers build the 3D models by m ... more

Abstract preview: This paper describes ongoing work on creating a benchmarking and validation dataset for biological image segmentation. While the primary target is biological images, we believe that the dataset would ... more

Abstract preview: Image segmentation is the partitioning of an image into meaningful regions or pixel groups and is a necessary prerequisite for many higher level computer vision tasks, such as object recognition, scen ... more

Abstract preview: Variational cost functions that are based on pairwise similarity between pixels can be minimized within level set framework resulting in a binary image segmentation. In this paper we extend such cost ... more

Abstract preview: We present a new shape prior segmentation method using graph cuts capable of segmenting multiple objects. The shape prior energy is based on a shape distance popular with level set approaches. We also ... more

Abstract preview: The main goal of this dissertation is the development and discussion of techniques for higher-level image analysis, i.e., object-level analysis, of breast cancer imagery. Established cytologic (cell) ... more

Abstract preview: The utility of nuclear features for automated cancer diagnosis has been well established. Use of cytoplasm and stroma features, however, has not been addressed in an computeraided diagnosis system, al ... more

Abstract preview: Analyzing cell viability is crucial in understanding the underlying molecular mechanisms of disease. With more than 20 million cases worldwide, Alzheimer's disease (AD) is now the most common neu ... more

Abstract preview: The notochord is an embryonic structure that undergoes dramatic cell shape changes as it itself changes shape from a roughly isodiametric primordium of mesenchymal cells to a long extended rod. Ascidi ... more

Abstract preview: Identification of cell nuclei is a fundamental operation,and nuclei centroids are used in a wide gamut of biological and medical analysis. Many methods exist for semi-automated and automated counting ... more

Abstract preview: Biological images are critical components for a detailed understanding of the structure and functioning of cells and proteins. Image processing and analysis tools increasingly play a significant role ... more

Abstract preview: A variational approach for the background/foreground segmentation of multiple views of the same scene is presented. The main novelty is the introduction of cost functions based on pairwise similarity ... more

Abstract preview: We introduce a framework for image enhancement, which smooths images while preserving edge information. Domain (spatial) and range (feature) information are combined in one single measure in a princip ... more

Abstract preview: Tracing of curvilinear structures is one of the fundamental tools in the quantitative analysis of biological images, for extracting information about structures such as blood vessels, neurons, microtu ... more

Abstract preview: One of the main challenges in image segmentation is to adapt prior knowledge about the objects/regions that are likely to be present in an image, in order to obtain more precise detection and recognit ... more

Abstract preview: The expression levels of rod opsin and glial fibrillary acidic protein (GFAP) capture important structural changes in the retina during injury and recovery. Quantitatively measuring these expression l ... more

Abstract preview: Microtubule (MT) dynamics are traditionally analyzed from time lapse images by manual techniques that are laborious, approximate and often limited. Recently, computer vision techniques have been appli ... more

Abstract preview: In this paper we introduce new type of variational segmentation cost functions and associated active contour methods that are based on pairwise similarities or dissimilarities of the pixels. As a solu ... more

Abstract preview: A novel framework for pruning a category of images is proposed in this paper. We assume no prior information about the contents or semantics of the images. Our framework discovers consistencies and kn ... more

Abstract preview: In this paper, we propose a novel multi-scale edge detection and vector field design scheme. We show that using multiscale techniques edge detection and segmentation quality on natural images can be i ... more

Abstract preview: We introduce robust variational segmentation techniques that are driven by an Edgeflow vector field. Variational image segmentation has been widely used during the past ten years. While there is a ric ... more

Abstract preview: We propose in this paper an interactive segmentation algorithm based on curve evolution techniques. The task of automated segmentation has proven to be highly complex and application dependent. User&# ... more

Abstract preview: The primary goal of this thesis is to develop robust image segmentation methods based on variational techniques. Image segmentation is one of the fundamental problems in image processing and computer ... more

Abstract preview: Our contribution in this paper is two-fold. First, we extend our previous curve evolution method based on pairwise similarities. This curve evolution equation combines the grouping abilities of active ... more

Abstract preview: A novel scheme for image segmentation is presented. An image segmentation criterion is proposed that groups similar pixels together to form regions. This criterion is formulated as a cost function. Th ... more

Abstract preview: We propose a video region segmentation scheme combin-ing spatio-temporal edges and watershed techniques. We consider the video sequence as a 3-D volume and compute color edges within this volume. Thes ... more

Abstract preview: An image segmentation scheme that utilizes image-based flow fields in a curve evolution framework is presented. Geometric curve evolution methods require an edge function and a vector field with certa ... more

Abstract preview: A novel scheme for image segmentation is presented. An image segmentation criterion is proposed that gathers similar pixels together to form regions and creates boundaries between two dissimilar regio ... more

Abstract preview: A novel scheme for image segmentation is presented. The technique is based on the integration of ideas from geodesic active contours and a recently proposed edgeflow segmentation. Given an image a 2-D ... more

Abstract preview: A novel boundary detection scheme based on "edge flow" is proposed in this paper. This scheme utilizes a predictive coding model to identify the direction of change in color and texture at ... more

Abstract preview: In this work, a new approach to fully automatic color image segmentation, called JSEG, is presented. First, col-ors in the image are quantized to several representing classes that can be used to diffe ... more

Abstract preview: A general variational framework for image approximation and segmentation is introduced. By using a continuous "line-process" to represent edge boundaries, it is possible to formulate a varia ... more

Abstract preview: A novel boundary detection scheme based on "edge flow" is proposed in this paper. This scheme utilizes a predictive coding model to identify the direction of change in color and tecture at ... more

Abstract preview: A general variational framework for image approximation and segmentation is introduced in which the boundary function has a simple explicit form in terms of the approximation function. At the same tim ... more