Optimizing Large Sets of Image Data

Targeted CE per ARRT’s Discipline, Category, and Subcategory classification for enrollments starting after June 11, 2024:
[Note: Discipline-specific Targeted CE credits may be less than the total Category A credits approved for this course.]

Computed Tomography: 0.75
Image Production: 0.75
Image Formation: 0.75

Mammography: 0.75
Image Production: 0.75
Image Acquisition and Quality Assurance: 0.75

Magnetic Resonance Imaging: 0.75
Image Production: 0.75
Sequence Parameters and Options: 0.75

Nuclear Medicine Technology: 0.75
Image Production: 0.75
Instrumentation: 0.75

Registered Radiologist Assistant: 3.00
Procedures: 3.00
Abdominal Section: 0.75
Thoracic Section: 0.75
Musculoskeletal and Endocrine Sections: 0.75
Neurological, Vascular, and Lymphatic Sections: 0.75

Outline

1. Introduction
2. Historical Overview
   1. Analog Era
   2. Early Digital Era
   3. Current Era
3. Radiologists’ Visual and Interpretative Tasks
   1. Detection and Localization
   2. Change Assessment
   3. Target Characterization
   4. Communicating Results
   5. Image-guided Interventions
4. Use of Advanced Technologies to Aid Radiologists
   1. Visualization Tools that Facilitate Data Reduction
   2. Advanced Postprocessing Workflow and Hanging Protocols
   3. Tools that Facilitate Navigation through Large Numbers of Images
   4. Technology Tools that Speed Image Rendering
   5. Tools that Facilitate Distribution of Images and Reports to Referring Physicians
   6. Tools to Transform Modern Image Management
5. Conclusions

Objectives

Upon completion of this course, students will:

1. be familiar with the imaging modalities that are providing large data sets
2. be familiar with the processes involved with image interpretation
3. identify the variables used for analog image exposure techniques
4. identify processes used for overcoming the wide dynamic range of digital images in order to print them on film
5. identify the need for an image viewing paradigm shift
6. identify the parameter that allows true 3D volume production
7. be familiar with the properties of isotropic voxels
8. be familiar with the viewing options available for interpretation of image studies
9. identify challenges for study interpretation using current methods of acquisition
10. be familiar with the individual tasks involved in image interpretation
11. identify error potential for interpretive tasks
12. be familiar with error rates for interpretive tasks
13. understand standards of quantifying target visibility during interpretation
14. be familiar with signal to noise threshold for target detection
15. understand computer aided detection (CAD) and its usefulness
16. be familiar with error rates for CAD during target detection
17. identify criteria used for change assessment during interpretaion
18. be familiar with technologies that can be applied to improve change assessment
19. be familiar with the individual tasks involved in image interpretation
20. know the individual tasks involved in image interpretation
21. be familiar with data quantities required for different parts of the image data set
22. name the national and professional organizations working to overcome issues dealing with large data sets
23. identify the tool used to restore the gestalt exam view during interpretation
24. be familiar with stereoscopy principles used for image viewing
25. understand the technology used for head and eye tracking during image viewing
26. identify the minimum computing power needed to produce 3D renderings
27. explain the methods for easily viewing many thin section slabs of rendered data
28. identify uses for curved planar reformations
29. be familiar with the principles of 3D image viewing
30. be familiar with the principles of fusion imaging
31. identify disadvantages of using historic image viewing and navigation tools
32. identify alternative tools for image viewing and navigation
33. understand the advantages of using improved interpretation and data distribution processes
34. identify current innovations in data distribution
35. be familiar with data identified as non-imaging clinical information