skip to main content
OSTI.GOV title logo U.S. Department of Energy
Office of Scientific and Technical Information

Title: Preprocessing Strategies to Improve MCR Analyses of Hyperspectral Images.

Abstract

Abstract not provided.

Authors:
; ; ; ; ;
Publication Date:
Research Org.:
Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
Sponsoring Org.:
USDOE National Nuclear Security Administration (NNSA)
OSTI Identifier:
1106801
Report Number(s):
SAND2011-7649J
464938
DOE Contract Number:
AC04-94AL85000
Resource Type:
Journal Article
Resource Relation:
Journal Name: CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS; Related Information: Proposed for publication in CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS.
Country of Publication:
United States
Language:
English

Citation Formats

Jones, Howland D. T., Haaland, David M., Sinclair, Michael B., Melgaard, David Kennett, Collins, Aaron M, and Timlin, Jerilyn A.. Preprocessing Strategies to Improve MCR Analyses of Hyperspectral Images.. United States: N. p., 2011. Web.
Jones, Howland D. T., Haaland, David M., Sinclair, Michael B., Melgaard, David Kennett, Collins, Aaron M, & Timlin, Jerilyn A.. Preprocessing Strategies to Improve MCR Analyses of Hyperspectral Images.. United States.
Jones, Howland D. T., Haaland, David M., Sinclair, Michael B., Melgaard, David Kennett, Collins, Aaron M, and Timlin, Jerilyn A.. Sat . "Preprocessing Strategies to Improve MCR Analyses of Hyperspectral Images.". United States. doi:.
@article{osti_1106801,
title = {Preprocessing Strategies to Improve MCR Analyses of Hyperspectral Images.},
author = {Jones, Howland D. T. and Haaland, David M. and Sinclair, Michael B. and Melgaard, David Kennett and Collins, Aaron M and Timlin, Jerilyn A.},
abstractNote = {Abstract not provided.},
doi = {},
journal = {CHEMOMETRICS AND INTELLIGENT LABORATORY SYSTEMS},
number = ,
volume = ,
place = {United States},
year = {Sat Oct 01 00:00:00 EDT 2011},
month = {Sat Oct 01 00:00:00 EDT 2011}
}
  • Purpose: Computed tomography (CT) streak artifacts caused by metallic implants remain a challenge for the automatic processing of image data. The impact of metal artifacts in the soft-tissue region is magnified in cone-beam CT (CBCT), because the soft-tissue contrast is usually lower in CBCT images. The goal of this study was to develop an effective offline processing technique to minimize the effect. Methods and Materials: The geometry calibration cue of the CBCT system was used to track the position of the metal object in projection views. The three-dimensional (3D) representation of the object can be established from only two user-selectedmore » viewing angles. The position of the shadowed region in other views can be tracked by projecting the 3D coordinates of the object. Automatic image segmentation was used followed by a Laplacian diffusion method to replace the pixels inside the metal object with the boundary pixels. The modified projection data were then used to reconstruct a new CBCT image. The procedure was tested in phantoms, prostate cancer patients with implanted gold markers and metal prosthesis, and a head-and-neck patient with dental amalgam in the teeth. Results: Both phantom and patient studies demonstrated that the procedure was able to minimize the metal artifacts. Soft-tissue visibility was improved near or away from the metal object. The processing time was 1-2 s per projection. Conclusion: We have implemented an effective metal artifact-suppressing algorithm to improve the quality of CBCT images.« less
  • Purpose: To modify the preprocessing technique, which was previously proposed, improving compressibility of computed tomography (CT) images to cover the diversity of three dimensional configurations of different body parts and to evaluate the robustness of the technique in terms of segmentation correctness and increase in reversible compression ratio (CR) for various CT examinations.Methods: This study had institutional review board approval with waiver of informed patient consent. A preprocessing technique was previously proposed to improve the compressibility of CT images by replacing pixel values outside the body region with a constant value resulting in maximizing data redundancy. Since the technique wasmore » developed aiming at only chest CT images, the authors modified the segmentation method to cover the diversity of three dimensional configurations of different body parts. The modified version was evaluated as follows. In randomly selected 368 CT examinations (352 787 images), each image was preprocessed by using the modified preprocessing technique. Radiologists visually confirmed whether the segmented region covers the body region or not. The images with and without the preprocessing were reversibly compressed using Joint Photographic Experts Group (JPEG), JPEG2000 two-dimensional (2D), and JPEG2000 three-dimensional (3D) compressions. The percentage increase in CR per examination (CR{sub I}) was measured.Results: The rate of correct segmentation was 100.0% (95% CI: 99.9%, 100.0%) for all the examinations. The median of CR{sub I} were 26.1% (95% CI: 24.9%, 27.1%), 40.2% (38.5%, 41.1%), and 34.5% (32.7%, 36.2%) in JPEG, JPEG2000 2D, and JPEG2000 3D, respectively.Conclusions: In various CT examinations, the modified preprocessing technique can increase in the CR by 25% or more without concerning about degradation of diagnostic information.« less
  • Hyperspectral images consist of large number of bands which require sophisticated analysis to extract. One approach to reduce computational cost, information representation, and accelerate knowledge discovery is to eliminate bands that do not add value to the classification and analysis method which is being applied. In particular, algorithms that perform band elimination should be designed to take advantage of the structure of the classification method used. This letter introduces an embedded-feature-selection (EFS) algorithm that is tailored to operate with support vector machines (SVMs) to perform band selection and classification simultaneously. We have successfully applied this algorithm to determine a reasonablemore » subset of bands without any user-defined stopping criteria on some sample AVIRIS images; a problem occurs in benchmarking recursive-feature-elimination methods for the SVMs.« less