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Title: X-ray fluoroscopy spatio-temporal filtering with object detection

Abstract

One potential way to reduce patient and staff x-ray fluoroscopy dose is to reduce the quantum exposure to the detector and compensate the additional noise with digital filtering. A new filtering method, spatio-temporal filtering with object detection, is described that reduces noise while minimizing motion and spatial blur. As compared to some conventional motion-detection filtering schemes, this object-detection method incorporates additional a priori knowledge of image content; i.e. much of the motion occurs in isolated long thin objects (catheters, guide wires, etc.). The authors create object-likelihood images and use these to control spatial and recursive temporal filtering such as to reduce blurring the objects of interest. They use automatically computed receiver operating characteristic (ROC) curves to optimize the object-likelihood enhancement method and determine that oriented matched filter kernels with 4 orientations are appropriate. The matched filter kernels are simple projected cylinders. The authors demonstrate the method on several representative x-ray fluoroscopy sequences to which noise is added to simulate very low dose acquisitions. With processing, they find that noise variance is significantly reduced with slightly less noise reduction near moving objects. They estimate an effective exposure reduction greater than 80%.

Authors:
 [1];  [1]
  1. Case Western Reserve Univ., Cleveland, OH (United States). Dept. of Biomedical Engineering
Publication Date:
OSTI Identifier:
182943
Resource Type:
Journal Article
Journal Name:
IEEE Transactions on Medical Imaging
Additional Journal Information:
Journal Volume: 14; Journal Issue: 4; Other Information: PBD: Dec 1995
Country of Publication:
United States
Language:
English
Subject:
55 BIOLOGY AND MEDICINE, BASIC STUDIES; 56 BIOLOGY AND MEDICINE, APPLIED STUDIES; BIOMEDICAL RADIOGRAPHY; NOISE; FILTERS; X RADIATION; DOSIMETRY; DESIGN; IMAGE PROCESSING; RADIATION DOSES

Citation Formats

Aufrichtig, R, Wilson, D L, and University Hospitals of Cleveland, OH. X-ray fluoroscopy spatio-temporal filtering with object detection. United States: N. p., 1995. Web. doi:10.1109/42.476114.
Aufrichtig, R, Wilson, D L, & University Hospitals of Cleveland, OH. X-ray fluoroscopy spatio-temporal filtering with object detection. United States. doi:10.1109/42.476114.
Aufrichtig, R, Wilson, D L, and University Hospitals of Cleveland, OH. Fri . "X-ray fluoroscopy spatio-temporal filtering with object detection". United States. doi:10.1109/42.476114.
@article{osti_182943,
title = {X-ray fluoroscopy spatio-temporal filtering with object detection},
author = {Aufrichtig, R and Wilson, D L and University Hospitals of Cleveland, OH},
abstractNote = {One potential way to reduce patient and staff x-ray fluoroscopy dose is to reduce the quantum exposure to the detector and compensate the additional noise with digital filtering. A new filtering method, spatio-temporal filtering with object detection, is described that reduces noise while minimizing motion and spatial blur. As compared to some conventional motion-detection filtering schemes, this object-detection method incorporates additional a priori knowledge of image content; i.e. much of the motion occurs in isolated long thin objects (catheters, guide wires, etc.). The authors create object-likelihood images and use these to control spatial and recursive temporal filtering such as to reduce blurring the objects of interest. They use automatically computed receiver operating characteristic (ROC) curves to optimize the object-likelihood enhancement method and determine that oriented matched filter kernels with 4 orientations are appropriate. The matched filter kernels are simple projected cylinders. The authors demonstrate the method on several representative x-ray fluoroscopy sequences to which noise is added to simulate very low dose acquisitions. With processing, they find that noise variance is significantly reduced with slightly less noise reduction near moving objects. They estimate an effective exposure reduction greater than 80%.},
doi = {10.1109/42.476114},
journal = {IEEE Transactions on Medical Imaging},
number = 4,
volume = 14,
place = {United States},
year = {1995},
month = {12}
}