Biplane Correlation Imaging: A Feasibility Study Based on Phantom and Human Data.
The objective of this study was to implement and evaluate the performance of a biplane correlation imaging (BCI) technique aimed to reduce the effect of anatomic noise and improve the detection of lung nodules in chest radiographs. Seventy-one low-dose posterior-anterior images were acquired from an...
| Publicado en: | Journal of Digital Imaging Vol. 25; no. 1; pp. 137 - 148 |
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| Autores principales: | , , , |
| Formato: | diagnostic images pictorial research tables/charts Journal Article |
| Publicado: |
Springer Nature
Feb2012
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=104634128&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 104634128 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 08971889 DOQ jtl: Journal of Digital Imaging issn: 08971889 maglogo: N pubinfo: dt: Feb2012 vid: 25 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 104634128 70531108 10.1007/s10278-011-9392-z NLM21618054 PMC3264726 104634128 ppf: 137 ppct: 11 formats: fmt: @attributes: type: P tig: atl: Biplane Correlation Imaging: A Feasibility Study Based on Phantom and Human Data. aug: au: Samei, Ehsan Majdi-Nasab, Nariman Dobbins, James McAdams, H. affil: Carl E. Ravin Advanced Imaging Laboratories, Department of Radiology, Duke University, Durham 27710 USA sug: subj: Diagnosis, Computer Assisted Radiography, Thoracic Lung Pathology Diagnostic Imaging Methods Human Prospective Studies Phantoms, Imaging Data Analysis Software Adult Middle Age Aged Female Male Radiographic Image Interpretation, Computer-Assisted Funding Source Adult: 19-44 years Middle Aged: 45-64 years Aged: 65+ years Female Male ab: The objective of this study was to implement and evaluate the performance of a biplane correlation imaging (BCI) technique aimed to reduce the effect of anatomic noise and improve the detection of lung nodules in chest radiographs. Seventy-one low-dose posterior-anterior images were acquired from an anthropomorphic chest phantom with 0.28° angular separations over a range of ±10° along the vertical axis within an 11 s interval. Similar data were acquired from 19 human subjects with institutional review board approval and informed consent. The data were incorporated into a computer-aided detection (CAD) algorithm in which suspect lesions were identified by examining the geometrical correlation of the detected signals that remained relatively constant against variable anatomic backgrounds. The data were analyzed to determine the effect of angular separation, and the overall sensitivity and false-positives for lung nodule detection. The best performance was achieved for angular separations of the projection pairs greater than 5°. Within that range, the technique provided an order of magnitude decrease in the number of false-positive reports when compared with CAD analysis of single-view images. Overall, the technique yielded ~1.1 false-positive per patient with an average sensitivity of 75%. The results indicated that the incorporation of angular information can offer a reduction in the number of false-positives without a notable reduction in sensitivity. The findings suggest that the BCI technique has the potential for clinical implementation as a cost-effective technique to improve the detection of subtle lung nodules with lowered rate of false-positives. pubtype: Academic Journal doctype: diagnostic images pictorial research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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