Literature DB >> 12598025

3-D imaging with MDCT.

Geoffrey D Rubin1.   

Abstract

Without doubt, the greatest challenge of multidetector-row CT is dealing with 'data explosion'. For our carotid/intracranial CT angiograms, we routinely have 375 images to review (300 mm coverage reconstructed every 0.8 mm); for aortic studies we have 450-500 images ( approximately 600 mm coverage reconstructed every 1.3 mm); and for a study of the lower extremity inflow and run-off, we may generate 900-1000 transverse reconstructions. While we could reconstruct fewer images for these data, experience with single-detector row CT scanners indicates that longitudinal resolution and disease detection is improved when at least 50% overlap of cross-sections is generated [Radiology 200 (1996) 312]. If we are to optimize our clinical protocols and take full advantage of these CT scanners, we will need to change the way that we interpret, transfer, and store CT data. Film is no longer a viable option. Workstation based review of transverse reconstructions for interpretation is a necessity, but the workstations must improve to provide efficient access to these data, and we must have a way of providing our clinicians with images that can be transported to clinics and the operating room. Alternative visualization and analysis using volumetric tools, including 3-D visualization must evolve from luxury to necessity. We cannot rest on historical precedent to interpret these near isotropically sampled volumetric data using transverse reconstructions alone [Radiology 173 (1989) 527]. Although the tools for volumetric analysis on 3-D workstations have evolved over recent years, they have probably not yet evolved to a level that routine interpretation can be performed as efficiently and accurately as transverse section review. Both hardware and software developments must occur. While current computer workstations and visualization software are certainly adequate for assessing these MDCT data volumetrically, the process is very time consuming. What follows are a description of current workstation capabilities and a brief discussion of where development needs to go to facilitate the complete integration of volumetric analysis into the interpretive process of CT data.

Mesh:

Year:  2003        PMID: 12598025     DOI: 10.1016/s0720-048x(03)00035-4

Source DB:  PubMed          Journal:  Eur J Radiol        ISSN: 0720-048X            Impact factor:   3.528


  14 in total

Review 1.  Cardiac and vascular MDCT: thoracic imaging.

Authors:  Andreas F Kopp; Axel Küttner; Tobias Trabold; Martin Heuschmid; Stephen Schröder; C D Claussen
Journal:  Eur Radiol       Date:  2003-12       Impact factor: 5.315

2.  Irreversible JPEG 2000 compression of abdominal CT for primary interpretation: assessment of visually lossless threshold.

Authors:  Kyoung Ho Lee; Young Hoon Kim; Bo Hyoung Kim; Kil Joong Kim; Tae Jung Kim; Hyuk Jung Kim; Seokyung Hahn
Journal:  Eur Radiol       Date:  2006-11-22       Impact factor: 5.315

3.  On-the-fly generation of multiplanar reformation images independent of CT scanner type.

Authors:  Dong Kyun Jeong; Kyoung Ho Lee; Bo Hyoung Kim; Kil Joong Kim; Young Hoon Kim; Vasundhara Bajpai; Yeong Gil Shin
Journal:  J Digit Imaging       Date:  2007-03-24       Impact factor: 4.056

4.  Simplifying the exploration of volumetric images: development of a 3D user interface for the radiologist's workplace.

Authors:  M Teistler; R S Breiman; T Lison; O J Bott; D P Pretschner; A Aziz; W L Nowinski
Journal:  J Digit Imaging       Date:  2008-10       Impact factor: 4.056

5.  The Lung Image Database Consortium (LIDC): an evaluation of radiologist variability in the identification of lung nodules on CT scans.

Authors:  Samuel G Armato; Michael F McNitt-Gray; Anthony P Reeves; Charles R Meyer; Geoffrey McLennan; Denise R Aberle; Ella A Kazerooni; Heber MacMahon; Edwin J R van Beek; David Yankelevitz; Eric A Hoffman; Claudia I Henschke; Rachael Y Roberts; Matthew S Brown; Roger M Engelmann; Richard C Pais; Christopher W Piker; David Qing; Masha Kocherginsky; Barbara Y Croft; Laurence P Clarke
Journal:  Acad Radiol       Date:  2007-11       Impact factor: 3.173

6.  Summation or axial slab average intensity projection of abdominal thin-section CT datasets: can they substitute for the primary reconstruction from raw projection data?

Authors:  Kyoung Ho Lee; Helen Hong; Seokyung Hahn; Bohyoung Kim; Kil Joong Kim; Young Hoon Kim
Journal:  J Digit Imaging       Date:  2007-09-06       Impact factor: 4.056

7.  Technical developments in postprocessing of paediatric airway imaging.

Authors:  Savvas Andronikou; Benjamin Irving; Linda Tebogo Hlabangana; Tanyia Pillay; Paul Taylor; Pierre Goussard; Robert Gie
Journal:  Pediatr Radiol       Date:  2013-02-16

Review 8.  3D-CT anatomy for VATS segmentectomy.

Authors:  Kimihiro Shimizu; Seshiru Nakazawa; Toshiteru Nagashima; Hiroyuki Kuwano; Akira Mogi
Journal:  J Vis Surg       Date:  2017-07-01

9.  Use of a Dedicated Server to Perform Coronal and Sagittal Reformations in Trauma Examinations.

Authors:  Jason N Itri; William W Boonn
Journal:  J Digit Imaging       Date:  2010-04-15       Impact factor: 4.056

10.  Automatic definition of the central-chest lymph-node stations.

Authors:  Kongkuo Lu; Pinyo Taeprasartsit; Rebecca Bascom; Rickhesvar P M Mahraj; William E Higgins
Journal:  Int J Comput Assist Radiol Surg       Date:  2011-02-27       Impact factor: 2.924

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