How To Use PIAAA
Analyse digital images (DICOM format)
Load the PIAAA program then simply open the DICOM image and perform the fully automated analysis with a single click of the mouse.
Analyse film images (acquire images using a film scanner)
Put the phantom film (18x24 cm) in the frame of the Phantom Mask (a plastic or cardboard frame supplied on request which includes a calibration strip) and place on the film scanner. PIAAA recognises the orientation of the film. Select the appropriate phantom from the drop down menu, and that is all! PIAAA takes a few minutes to perform its task and show you the final results. Another click is sufficient to send the data to your supervision centre (if used).
Load the PIAAA program then simply open the DICOM image and perform the fully automated analysis with a single click of the mouse.
Analyse film images (acquire images using a film scanner)
Put the phantom film (18x24 cm) in the frame of the Phantom Mask (a plastic or cardboard frame supplied on request which includes a calibration strip) and place on the film scanner. PIAAA recognises the orientation of the film. Select the appropriate phantom from the drop down menu, and that is all! PIAAA takes a few minutes to perform its task and show you the final results. Another click is sufficient to send the data to your supervision centre (if used).
Advanced Users
Previous versions of PIAAA were based on the assumption that the images were acquired for routine Quality Control purposes according to the Leeds Test Objects user manual.
The aim of the software was to increase the efficiency and the reliability of constancy tests for image quality by providing the user with a fully automatic process when assessing the long-term performance of radiological systems. Algorithms for fully automatic recognition were necessarily optimised only to cope with images satisfying well-defined constraints inherent to the above purpose.
Growing interest in the use of test objects for other purposes means new adaptive algorithms are required to process images acquired with exposure conditions and/or phantom orientation not compliant with Leeds Test Object Manuals, images “For Presentation”, images with different magnifications (especially for TO18FG when used in combination with zooming facilities of X-Ray Image Intensifier Systems).
The task is not easy because in principle, through image processing and filtering, any kind of image can be obtained. In previous versions of PIAAA, fully automatic recognition requires that images satisfy some initial constraints. This new version intends to extend the use of the software for optimisation of radiological equipment and comparison of performance among radiological equipments. In the case of optimisation, several images acquired with the same equipment in different conditions and/or exposure settings are compared to determine the best compromise between image quality and dose. Comparison of performance among radiological equipments is possible when images of the same test object are acquired in the same conditions with different equipments.
The aim of the software was to increase the efficiency and the reliability of constancy tests for image quality by providing the user with a fully automatic process when assessing the long-term performance of radiological systems. Algorithms for fully automatic recognition were necessarily optimised only to cope with images satisfying well-defined constraints inherent to the above purpose.
Growing interest in the use of test objects for other purposes means new adaptive algorithms are required to process images acquired with exposure conditions and/or phantom orientation not compliant with Leeds Test Object Manuals, images “For Presentation”, images with different magnifications (especially for TO18FG when used in combination with zooming facilities of X-Ray Image Intensifier Systems).
The task is not easy because in principle, through image processing and filtering, any kind of image can be obtained. In previous versions of PIAAA, fully automatic recognition requires that images satisfy some initial constraints. This new version intends to extend the use of the software for optimisation of radiological equipment and comparison of performance among radiological equipments. In the case of optimisation, several images acquired with the same equipment in different conditions and/or exposure settings are compared to determine the best compromise between image quality and dose. Comparison of performance among radiological equipments is possible when images of the same test object are acquired in the same conditions with different equipments.
Hardware requirements
The maximum optical density that can be accurately evaluated depends on the scanner specifications. It should be not less than 3.0 OD in order to appropriately estimate the average gradient of a sensitometric strip. The resolution limit that can be approached is dependent on the optical resolution of the scanner. Typically, a scanner with an optical resolution of 1200 dpi has a resolution limit of about 10 lp/mm.
Scanner requirements:
Optical Resolution 600 x 1200 dpi
Bit Depth 36-bit Input and Output
Maximum Density 3.0 D
Scan Area 203mm x 254mm (8" x 10") Transparency
Platform Windows
Driver TWAIN 1.7 compatible
PC System Requirements:
256MB RAM (512MB recommended)
Pentium PC or later
Windows 98SE/2000/ME/XP
100 MB of free space on hard-drive
Scanner requirements:
Optical Resolution 600 x 1200 dpi
Bit Depth 36-bit Input and Output
Maximum Density 3.0 D
Scan Area 203mm x 254mm (8" x 10") Transparency
Platform Windows
Driver TWAIN 1.7 compatible
PC System Requirements:
256MB RAM (512MB recommended)
Pentium PC or later
Windows 98SE/2000/ME/XP
100 MB of free space on hard-drive
