Qianjing Feng

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PURPOSE Though highly desirable in radiologic procedures, low-dose CT (LDCT) images tend to be severely degraded by quantum noise and non-stationary artifacts. The purpose of this paper is to improve the abdominal LDCT images by the approach of Weighted Intensity Averaging over Large-scale Neighborhoods (WIA-LN). MATERIALS AND METHODS In the(More)
Low-dose computed tomography (LDCT) images are often severely degraded by amplified mottle noise and streak artifacts. These artifacts are often hard to suppress without introducing tissue blurring effects. In this paper, we propose to process LDCT images using a novel image-domain algorithm called "artifact suppressed dictionary learning (ASDL)." In this(More)
Cerebral perfusion x-ray computed tomography (PCT) imaging, which detects and characterizes the ischemic penumbra, and assesses blood-brain barrier permeability with acute stroke or chronic cerebrovascular diseases, has been developed extensively over the past decades. However, due to its sequential scan protocol, the associated radiation dose has raised(More)
Minimal path techniques can efficiently extract geometrically curve-like structures by finding the path with minimal accumulated cost between two given endpoints. Though having found wide practical applications (e.g., line identification, crack detection, and vascular centerline extraction), minimal path techniques suffer from some notable problems. The(More)
The Web Access to Digital Imaging and Communication in Medicine (DICOM) Persistent Objects (WADO) standard specifies a Web-based service for accessing and presenting DICOM persistent objects, such as images and medical imaging reports. This paper analyzes the image transferring mechanism of the WADO service and proposes to extend its abilities by accessing(More)
Accurate prediction of CT image from MRI data is clinically desired for attenuation correction in PET/MR hybrid imaging systems and dose planning in MR-based radiation therapy. We present a k-nearest neighbor (KNN)regression method to predict CT image from MRI data. In this method the nearest neighbors of each MR image patch are searched in the constraint(More)
Although the quality of herbal medicine is tightly associated with plant genotype and location, microbial traits of most herbs remain unclear. In this study, bacterial communities residing Astragali Radix, which is derived from Astragalus membranaceus and A. mongholicus roots, have been characterized by automated ribosomal intergenic spacer analysis (ARISA)(More)
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