Coconuts, grapes, and peppers: Home-made models in the learning process of post-processing softwares used in computed-tomography (CT) imaging

Transcription

1 Coconuts, grapes, and peppers: Home-made models in the learning process of post-processing softwares used in computed-tomography (CT) imaging Poster No.: C-3019 Congress: ECR 2010 Type: Educational Exhibit Topic: Radiographers Authors: P. Caruso, E. Silvestri, E. Tagliafico, F. Adinolfi, M. Costa, B Giardina, S. Rombj, T. Luminati ; Genova/IT, Genoa/IT, San Donato Milanese/IT Keywords: natural models, post-processing software, MDCT DOI: /ecr2010/C-3019 Any information contained in this pdf file is automatically generated from digital material submitted to EPOS by third parties in the form of scientific presentations. References to any names, marks, products, or services of third parties or hypertext links to thirdparty sites or information are provided solely as a convenience to you and do not in any way constitute or imply ECR's endorsement, sponsorship or recommendation of the third party, information, product or service. ECR is not responsible for the content of these pages and does not make any representations regarding the content or accuracy of material in this file. As per copyright regulations, any unauthorised use of the material or parts thereof as well as commercial reproduction or multiple distribution by any traditional or electronically based reproduction/publication method ist strictly prohibited. You agree to defend, indemnify, and hold ECR harmless from and against any and all claims, damages, costs, and expenses, including attorneys' fees, arising from or related to your use of these pages. Please note: Links to movies, ppt slideshows and any other multimedia files are not available in the pdf version of presentations. Page 1 of 66

2 Learning objectives Learning objectives The purpose of our educational exhibit is to show the usefulness of home-made 'natural' models (such as fruit and vegetables) models in the learning process of post-processing softwares used in CT imaging. Background Background The learning process of the huge amount of functions included in new post-processing softwares used in CT imaging could be particularly difficult, especially for those operators who are not used to such kind of tools. In addition, a correct administration of radiation dose does not allow the acquisition of too many images in human subjects. Finally, a suboptimal knowledge of the human anatomy could even more slow down this process, particularly in those information-technology engineers who are responsible for software development. Being provided of layers with different attenuation values, the use of fruit and vegetables as a kind of biologic phantom could help to reduce these difficulties. Page 2 of 66

3 Data obtained from multislice CT were processed by a post-processing software (Voxar 3D). Page 3 of 66

4 Fig.: Display Software VOXAR 3D Page 4 of 66

5 References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 5 of 66

6 Fig.: Display Software VOXAR 3D Page 6 of 66

7 References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 7 of 66

8 Fig.: Display Software VOXAR 3D References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Images for this section: Page 8 of 66

9 Fig. 1: Display Software VOXAR 3D Page 9 of 66

10 Fig. 2: Display Software VOXAR 3D Page 10 of 66

11 Fig. 3: Display Software VOXAR 3D Page 11 of 66

12 Imaging findings OR Procedure details Image findings We will provide an extensive gallery of CT scans, multi-planar, three-dimensional surface and volume rendering, maximum intensity projection (MIP), minimum intensity projection (MinIP) reconstructions of coconuts, grapes, and peppers. We will correlate the images with the technical parameters of acquisition. We will provide the learning curve for each operator and for each function of the post-processing software. Multiplanar Reformatting (MPR):image data are taken from several axial slices and the reformatted image is displayed in sagittal, corona or oblique planes. Three Dimensional Shaded Surface: the user selects a threshold range; this allows the user to select only the tissue to be rendered Volume Rendering: is an advanced rendering thechnique that displays an entire volume set with control of the opacity or translucency of selected tissue. Maximum Intensity Projection: MIP in witch only maximum values are displayed; is a preferred method for CT angiography applications Minimum Intensity Projection: MinIP in witch only minimum values are displayed; can be used to demonstrate air-filled cavities. Page 12 of 66

13 Fig.: Coconuts: axial image References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 13 of 66

14 Fig.: Coconuts: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 14 of 66

15 Fig.: Coconuts: 3D Surface References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 15 of 66

16 Fig.: Coconuts: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 16 of 66

17 Fig.: Peppers: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 17 of 66

18 Fig.: Peppers: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 18 of 66

19 Fig.: Peppers: MIP References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 19 of 66

20 Fig.: Peppers: 3D Surface References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 20 of 66

21 Fig.: Peppers: Coronal MPR VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 21 of 66

22 Fig.: Grapes: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 22 of 66

23 Fig.: Grapes: coronal MPR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 23 of 66

24 Fig.: Grapes: MIP References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 24 of 66

25 Fig.: Grapes: 3D Surface References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 25 of 66

26 Images for this section: Fig. 1: Coconuts: axial image Page 26 of 66

27 Fig. 2: Coconuts: 3D VR Page 27 of 66

28 Fig. 3: Coconuts: 3D Surface Page 28 of 66

29 Fig. 4: Coconuts: 3D VR Page 29 of 66

30 Fig. 5: Peppers: 3D VR Page 30 of 66

31 Fig. 6: Peppers: 3D VR Page 31 of 66

32 Fig. 7: Peppers: MIP Page 32 of 66

33 Fig. 8: Peppers: 3D Surface Page 33 of 66

34 Fig. 9: Peppers: Coronal MPR VR Page 34 of 66

35 Fig. 10: Grapes: 3D VR Page 35 of 66

36 Fig. 11: Grapes: coronal MPR Page 36 of 66

37 Fig. 12: Grapes: MIP Page 37 of 66

38 Fig. 13: Grapes: 3D Surface Page 38 of 66

39 Conclusion Conclusion Post-processed images of natural models are presented in conjunction with anatomical structures such as brain, lung, kidney, and bowel. The use of home-made 'natural' models is extremely helpful in the learning process of post-processing softwares used in CT imaging. Page 39 of 66

40 Fig.: Coconuts: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Fig.: Scan of facial bones: 3D VR Surface rendering References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 40 of 66

41 Fig.: Peppers: axial MIP References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 41 of 66

42 Fig.: Kidneys: axial MIP References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 42 of 66

43 Fig.: Peppers: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 43 of 66

44 Fig.: Kidneys: coronal MPR VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 44 of 66

45 Fig.: Kidney: axial oblique MPR VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 45 of 66

46 Fig.: Grapes: minimum intensity projections (MinIP) References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 46 of 66

47 Fig.: Lungs: minimum intensity projections (MinIP) References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 47 of 66

48 Fig.: Grapes: 3D VR References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 48 of 66

49 Fig.: Colon: 3D VR Page 49 of 66

50 References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Fig.: Grapes: 3D Surface References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 50 of 66

51 Fig.: Lungs: 3D Surface References: T. Luminati; Unit of Radiology, Ospedale Evangelico Internazionale, Genova, ITALY Page 51 of 66

52 Images for this section: Fig. 1: Coconuts: 3D VR Page 52 of 66

53 Fig. 2: Scan of facial bones: 3D VR Surface rendering Page 53 of 66

54 Fig. 3: Peppers: axial MIP Page 54 of 66

55 Fig. 4: Kidneys: axial MIP Page 55 of 66

56 Fig. 5: Peppers: 3D VR Page 56 of 66

57 Fig. 6: Kidneys: coronal MPR VR Page 57 of 66

58 Fig. 7: Kidney: axial oblique MPR VR Page 58 of 66

59 Fig. 8: Lungs: minimum intensity projections (MinIP) Page 59 of 66

60 Fig. 9: Grapes: minimum intensity projections (MinIP) Page 60 of 66

61 Fig. 10: Grapes: 3D VR Page 61 of 66

62 Fig. 11: Colon: 3D VR Page 62 of 66

63 Fig. 12: Grapes: 3D Surface Page 63 of 66

64 Fig. 13: Lungs: 3D Surface Page 64 of 66

65 Personal Information T. Luminati Radiographer Department of Radiology Ospedale Evangelico Internazionale Genova - Italy tluminati@oeige.org F. Adinolfi, M. Costa, B. Giardina, S. Rombj, E. Tagliafico Radiographer Department of Radiology Ospedale Evangelico Internazionale Genova - Italy P. Caruso, E. Silvestri Radiologist Department of Radiology Ospedale Evangelico Internazionale Genova - Italy References,,,,,,. Istituto di Radiologia, Università Cattolica del S. Cuore, Policlinico A. Gemelli, Roma, Italy. Page 65 of 66

66 Post-processing of digital images. Rays Jan-Mar;28(1): John R. Haaga, V. S. Dogra, M. Forsting, R. C. Gilkeson, H. Kwon Ha, M. Sundaram CT and MRI of the whole body - fith edition,,. Department of Radiology, University of Parma, Italy. pavone@unipr.it From maximum intensity projection to volume rendering. Semin Ultrasound CT MR Oct;22(5):413-9.,,. Department of Radiological Sciences, University of California, Los Angeles. Three-dimensional image display in medicine. J Digit Imaging May;3(2):69-80.,. Siemens Medical Systems Ultrasound Group, Issaquah, WA , USA. mkirch@sqi.com Increasing spiral CT benefits with postprocessing applications. Eur J Radiol Aug;28(1):39-54.,,. Department of Three-Dimensional Imaging, Massachusetts General Hospital, Harvard Medical School, 25 New Chardon Street, Suite 400, Boston, MA 02114, USA. Advanced postprocessing and the emerging role of computer-aided detection. Radiol Clin North Am Jan;47(1): Page 66 of 66