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1p/19q co-deletion is an important prognostic factor in low grade gliomas. However, determination of the 1p/19q status currently requires a biopsy. To overcome this, we investigate a radiogenomic classification using support vector machines to non-invasively predict the 1p/19q status from multimodal MRI data. Different approaches of predicting this status were compared: a direct approach which predicts...
Corneal nerves changes have been linked to damage caused by surgical interventions or prolonged contact lens wear. Furthermore nerve tortuosity has been shown to correlate with the severity of diabetic neuropathy. For these reasons there has been an increasing interest on the analysis of these structures. In this work we propose a novel, robust, and fast fully automatic algorithm capable of tracing...
Data imbalance is a common property in many medical and biological data and usually results in degraded generalization performance. In this article, we present a novel boosting method to address two important questions in learning from imbalanced dataset: how to maximize the performance of classifying the minority instances without compromising the performance for the majority instances? and how to...
This paper presents a novel solution toward the accurate and automatic cartilage segmentation with multi-contrast MR images based on pixel classification. The previous pixel classification based works for cartilage segmentation only rely on the labeling by a trained classifier, such as support vector machines (SVM) or k-nearest neighbors. However, these frameworks do not consider the spatial information...
This paper presents an algorithm using discriminative sparse representations to segment tissues in optical images of the uterine cervix. Because of the large variations in the image appearance caused by the changing of illumination and specular reflection, the different classes of color and texture features in optical images are often overlapped with each other. Using sparse representations they can...
In this paper, we introduce a new classifier ensemble approach, applied to tissue segmentation in optical images of the uterine cervix. Ensemble methods combine the predictions of a set of diverse classifiers. The main contribution of our approach is an effective way of combination based on each classifier's performance level-namely, the sensitivity p and specificity q, which also produces an optimal...
Prostate cancer is a leading cause of cancer death for men in the United States. There is currently no widely adopted accurate noninvasive method for localizing prostate cancer using imaging. If such as technique were available it could be used to guide biopsy, radiotheraphy and surgery. However, current imaging techniques are limited due to inability to detect cancers, intensity changes related to...
This paper presents an eye-gaze tracking system based on the image processing. All the computations are performed in software and the system just needs a PC camera attached to the user's computer. We first extract the facial regions form the images using the skin-color model and connected-component analysis. Then the eye regions are detected by employing the rules and area segmentation. After the...
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