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Current practices of assessing infants' pain depends on the observer's subjective and potentially inconsistent judgment and requires continuous monitoring by care providers. Therefore, pain may be misinterpreted or totally missed leading to misdiagnosis and over/under treatment. To address these shortcomings, current practices can be augmented with a machine-based assessment system that monitors various...
Computed tomography (CT) is widely used during diagnosis and treatment of Non-Small Cell Lung Cancer (NSCLC). Current computer-aided diagnosis (CAD) models, designed for the classification of malignant and benign nodules, use image features, selected by feature selectors, for making a decision. In this paper, we investigate automated selection of different image features informed by different nodule...
We report novel results of utilizing infant facial tissue distortion as a pain indicator in video-sequences of ten infants based on analysis of facial strain. Facial strain, which is used as the main feature for classification, is generated for each facial expression and then used to train two classifiers, k Nearest-Neighbors (KNN) and support vector machine (SVM) to classify infants' expressions...
To classify cervical cells as normal or cancer, the histological image must be segmented. After segmentation mean nuclear volume can be used to distinguish between normal and cancer cells. Due to the rapid reproduction of cancer cells, they have higher mean nuclear volume than typical normal cells. We propose a large ensemble of segmentations which separate normal and cancer cases based on the single...
We present a continuous 3D face authentication system that uses a RGB-D camera to monitor the accessing user and ensure that only the allowed user uses a protected system. At the best of our knowledge, this is the first system that uses 3D face images to accomplish such objective. By using depth images, we reduce the amount of user cooperation that is required by the previous continuous authentication...
Design-based (unbiased) stereology provides an accurate, precise, and efficient method to quantify morphological parameters of biological microstructures, such as the total number of three-dimensional (3D) objects (cells) in stained tissue sections. The current requirement for extensive user interaction with commercially available computerized stereology systems limits the throughput of data collection...
The problem of detection of label-noise in large datasets is investigated. We consider applications where data are susceptible to label error and a human expert is available to verify a limited number of such labels in order to cleanse the data. We show the support vectors of a Support Vector Machine (SVM) contain almost all of these noisy labels. Therefore, the verification of support vectors allows...
The aim of this study is to investigate a data mining approach to help assess consequences of oil spills in the maritime environment. The approach under investigation is based on detecting suspected oil droplets in the water column adjacent to the Deepwater Horizon oil spill. Our method automatically detects particles in the water, classifies them and provides an interface for visual display. The...
Typically, thousands of gene expression levels are recorded for a group of patients, leading to the situation where the number of features far exceeds the number of examples. To combat this, researchers would want to combine gene expression data collected at different sites into one data set to reduce the magnitude of the difference between the number of features (genes) and examples (samples). This...
We propose a method for the automatic spotting (temporal segmentation) of facial expressions in long videos comprising of macro- and micro-expressions. The method utilizes the strain impacted on the facial skin due to the non-rigid motion caused during expressions. The strain magnitude is calculated using the central difference method over the robust and dense optical flow field observed in several...
Many genes and a small number of samples are problematic characteristics of microarray datasets. We investigated the impact on classification accuracy of gene selection approaches on filtered-to-200-gene datasets. Four datasets were used with 3 filters: Student's t-test, information gain, and reliefF. We applied Iterative Feature Perturbation (IFP) and Recursive Feature Elimination (SVM-RFE) for further...
In this paper, we propose a method to model the material constants (Young's modulus) of the skin in subregions of the face from the motion observed in multiple facial expressions and present its relevance to an image analysis task such as face verification. On a public database consisting of 40 subjects undergoing some set of facial motions associated with anger, disgust, fear, happy, sad, and surprise...
A novel wire detection algorithm for use by unmanned aerial vehicles (UAV) in low altitude urban reconnaissance is presented. This is of interest to urban search and rescue and military reconnaissance operations. Detection of wires plays an important role, because thin wires are hard to discern by tele-operators and automated systems. Our algorithm is based on identification of linear patterns in...
This paper presents an algorithm that detects and tracks marine vessels in video taken by a nonstationary camera installed on an untethered buoy. The video is characterized by large inter-frame motion of the camera, cluttered background, and presence of compression artifacts. Our approach performs segmentation of ships in individual frames processed with a color-gradient filter. The threshold selection...
Biophotonic imaging can be used to characterize tumor growth in animal models. Estimation of the numbers and location of target cells is dependent on accurate segmentation of a target region from the background luminescence of the animal body. Existing software systems extract general regions of interest in complex images but can fail to detect details or faint regions of interest in the presence...
Registering features in multiple mammographic views is an important technique to improve breast cancer detection rate. However, nonrigid breast deformation during X-ray imaging poses a severe challenge to the conventional 2D registration methods. We present a method that utilizes a 3D model to facilitate two-view registration by predicting breast deformation. At first, a finite element model of a...
The success of forensic identification largely depends on the availability of strong evidence or traces that substantiate the prosecution hypothesis that a certain person is guilty of crime. In light of this, extracting subtle evidences which the criminals leave behind at the crime scene will be of valuable help to investigators. We propose a novel method of using strain pattern extracted from changing...
Detecting a horizon in an image is an important part of many image related applications such as detecting ships on the horizon, flight control, and port security. Most of the existing solutions for the problem only use image processing methods to identify a horizon line in an image. This results in good accuracy for many cases and is fast in computation. However, for some images with difficult environmental...
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