Literature DB >> 4063650

Detection of small focal lesions in CT images: effects of reconstruction filters and visual display windows.

P F Judy, R G Swensson.   

Abstract

The detectability of small, high-contrast lesions was measured on CT images, simulations of those obtained by the EMI Mark I scanner. Images were reconstructed using five reconstruction filters (kernels), which varied the image sharpness and noise level. Different sets of images were produced using various CT display windows, six different window sizes and four different display level settings. The measured lesion detectability for observers increased from 1.6 to 2.4 as the reconstruction kernel became smoother, and it decreased only slightly at the largest display window (1000 CT numbers wide). These effects were predicted by changes in the signal-to-noise ratio, as calculated for the lesion-matched filter applied to each set of physical CT images. This filter computes the cross-correlation of the CT image and the lesion profile at the specified possible locations for the lesion.

Mesh:

Year:  1985        PMID: 4063650     DOI: 10.1259/0007-1285-58-686-137

Source DB:  PubMed          Journal:  Br J Radiol        ISSN: 0007-1285            Impact factor:   3.039


  6 in total

Review 1.  Collimator design for single photon emission tomography.

Authors:  S C Moore; K Kouris; I Cullum
Journal:  Eur J Nucl Med       Date:  1992

2.  Comparison of a PACS workstation with conventional film for interpretation of neonatal examinations: a paired comparison study.

Authors:  E A Franken; W L Smith; K S Berbaum; S C Kao; Y Sato
Journal:  Pediatr Radiol       Date:  1991

3.  Human- and model-observer performance in ramp-spectrum noise: effects of regularization and object variability.

Authors:  C K Abbey; H H Barrett
Journal:  J Opt Soc Am A Opt Image Sci Vis       Date:  2001-03       Impact factor: 2.129

4.  Designing a radiology workstation: a focus on navigation during the interpretation task.

Authors:  D Beard
Journal:  J Digit Imaging       Date:  1990-08       Impact factor: 4.056

5.  Deep Learning-Based Automatic Assessment of Lung Impairment in COVID-19 Pneumonia: Predicting Markers of Hypoxia With Computer Vision.

Authors:  Yauhen Statsenko; Tetiana Habuza; Tatsiana Talako; Mikalai Pazniak; Elena Likhorad; Aleh Pazniak; Pavel Beliakouski; Juri G Gelovani; Klaus Neidl-Van Gorkom; Taleb M Almansoori; Fatmah Al Zahmi; Dana Sharif Qandil; Nazar Zaki; Sanaa Elyassami; Anna Ponomareva; Tom Loney; Nerissa Naidoo; Guido Hein Huib Mannaerts; Jamal Al Koteesh; Milos R Ljubisavljevic; Karuna M Das
Journal:  Front Med (Lausanne)       Date:  2022-07-26

6.  Feasibility of Pediatric Low-Dose Facial CT Reconstructed with Filtered Back Projection Using Adequate Kernels.

Authors:  Hye Ji; Sun Kyoung You; Jeong Eun Lee; So Mi Lee; Hyun-Hae Cho; Joon Young Ohm
Journal:  Taehan Yongsang Uihakhoe Chi       Date:  2021-08-27
  6 in total

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