Compressed digital image technology is fundamental to a variety of consumer electronics applications. Coded images are often accessed in part rather than in whole, by accessing spatial regions of interest (ROIs). In many application architectures, the decoding process to access each ROI may occur separately…
This paper presents an algorithm for content based medical image search, which allows querying by a specific region of interest. The user provides a bounding box for the region in a query image. The algorithm then retrieves images similar in content to the query with…
The growing use of MDCT scans has introduced the need for radiologists to read and interpret a huge number of images in their routine workflow. An efficient, fully automatic algorithm for anatomy segmentation is introduced, which promises to improve such workflow by enabling semantic navigation…
We introduce a new, efficient algorithm for the automatic detection and localization of anatomical structures within 3D CT images. Our algorithm builds upon recent randomized decision tree classifiers and produces accurate posterior probabilities for each of the classes (e.g. organ labels) in the training set.…
This paper presents a novel method for location recognition, which exploits an epitomic representation to achieve both high efficiency and good generalization. A generative model based on epitomic image analysis captures the appearance and geometric structure of an environment while allowing for variations due to…
This paper presents a new, parallel segmentation algorithm which enables radiologists to separate a region of interest from 2D or 3D images accurately and efficiently. This, in turn, enables fast and accurate area/volume measurements as well as the extraction of statistics for the selected region.…
JPEG XR is the newest image coding standard from the JPEG committee. It primarily targets the representation of continuous-tone still images such as photographic images and achieves high image quality, on par with JPEG 2000, while requiring low computational resources and storage capacity. Moreover, it…
A new algorithm is presented for the automatic segmentation and classification of brain tissue from 3D MR scans. It uses discriminative Random Decision Forest classification and takes into account partial volume effects. This is combined with correction of intensities for the MR bias field, in…
We present a novel multi-view stereo method designed for image-based rendering that generates piecewise planar depth maps from an unordered collection of photographs. First a discrete set of 3D plane candidates are computed based on a sparse point cloud of the scene (recovered by structure…
This paper addresses the issue of extracting contexts and answers of questions from post discussion of online forums. We propose a novel and unified model by customizing the structural Support Vector Machine method. Our customization has several attractive properties: (1) it gives a comprehensive graphical…
In this paper, we present a semi-supervised method for automatic speech act recognition in email and forums. The major challenge of this task is due to lack of labeled data in these two genres. Our method leverages labeled data in the Switchboard-DAMSL and the Meeting…
This paper presents an efficient inference algorithm of conditional random fields (CRFs) for large-scale data. Our key idea is to decompose the output label state into an active set and an inactive set in which most unsupported transitions become a constant. Our method unifies two…
