This paper proposes a patent retrieval method that consists of two processing stages. In Stage 1, analysis and retrieval methods to improve recall are applied. In Stage 2, the top N documents retrieved in Stage 1 are re-arranged by applying analysis and retrieval methods that consider the claim structure to improve precision. This paper gives an overview of this retrieval method and evaluates i...

Co-located optical and virtual colonoscopy images provide important clinical information during routine colonoscopy procedures. Tracking algorithms that rely on image features to align virtual and optical images can fail when they encounter blurry image sequences. This is a common occurrence in colonoscopy images, when the endoscope touches a wall or is immersed in fluid. We propose a region-fl...

We present a novel numerical method to the time-harmonic inverse medium scattering problem of recovering the refractive index from near-field scattered data. The approach consists of two stages, one pruning step of detecting the scatterer support, and one resolution enhancing step with mixed regularization. The first step is strictly direct and of sampling type, and faithfully detects the scatt...

We propose a two-stage training for the multilayer perceptron (MLP). The first stage is bottom-up, where we use a class separability measure to conduct hidden layer training and the least squared error criterion to train the output layer. The second stage is top-down, we use a criterion derived from classification error rate to further train the network weights. We demonstrate the effectiveness...

Evaluation of stage of liver fibrosis in chronic type C hepatitis is very important in patient therapy. Commonly used method for fibrosis stage determination is liver biopsy, but it is an invasive method and also single biopsy does not give the confidence thus it is required to retrieve samples from more than one region of liver [1]. Some non-invasive tests methods are also available, but are e...

BACKGROUND In epidemiologic studies, cancer stage is an important predictor of outcomes. However, cancer stage is typically unavailable in medical insurance claims datasets, thus limiting the usefulness of such data for epidemiologic studies. Therefore, we sought to develop an algorithm to predict cancer stage based on covariates available from claims-based data. METHODS We identified a cohor...

We present a novel numerical method to the time-harmonic inverse medium scattering problem of recovering the refractive index from noisy near-field scattered data. The approach consists of two stages, one pruning step of detecting the scatterer support, and one resolution enhancing step with nonsmooth mixed regularization. The first step is strictly direct and of sampling type, and it faithfull...

Learning to rank (L2R) algorithms use a labeled training set to generate a ranking model that can later be used to rank new query results. These training sets are costly and laborious to produce, requiring human annotators to assess the relevance or order of the documents in relation to a query. Active learning algorithms are able to reduce the labeling effort by selectively sampling an unlabel...

This paper demonstrates the use of a simple but effective color-based inspection method in parquet slab grading. The approach is to divide the image to small rectangular regions and calculate color percentile features from these areas. Classification is performed in two stages, defect detection and recognition. The recognition results are further used in determining the final grade for the parq...

Mass lesion segmentation on mammograms is a challenging task since mass lesions are usually embedded and hidden in varying densities of parenchymal tissue structures. In this article, we present a method for automatic delineation of lesion boundaries on digital mammograms. This method utilizes a geometric active contour model that minimizes an energy function based on the homogeneities inside a...