IndoQCT 22a software features :

Features

The summary of IndoQCT features is shown in Figure 1. Basically, the features in IndoQCT are divided into two categories, namely main and additional features.

Main Features of IndoQCT

In accordance with IndoQCT’s initial vision, the main features presented are the automation of CT image quality measurements on various types of phantoms using a user-friendly Graphical User Interface (GUI). In version 22a, the covered phantoms are as follows:

• AAPM CT performance phantom (model 610, CIRS Inc, VA, USA)
• ACR CT accreditation phantom (Gammex Inc, Middleton, WI, USA)
• Catphan® phantom (Catphan 500, 504, 604, The Phantom Lab, NY, USA)
• GE CT QA phantom (GE Healthcare, Milwaukee, WI, USA)
• Canon TOS phantom (Canon Medical System, CA, USA)
• Siemens CT phantom (Siemens Healthcare, Erlangen, Germany)
• Philips CT QA phantom (Philips Medical System, Cleveland, OH, USA)
• Neusoft CT phantom (Neusoft Medical System, Shenyang, China)
• Hitachi CT phantom (Hitachi Ltd., Tokyo, Japan)

In addition to commercial phantoms already on the market and factory default phantoms, IndoQCT can also generate synthetic images using a computational approach. We call this as a computational phantom. This phantom is useful for educational purposes.

The image quality parameters presented in the main features of IndoQCT include parameters that are already known and standardized by many international agencies, as well as those that are still relatively new, as follows:

• CT number
• Noise
• CT number linearity
• Spatial resolution
• Slice thickness
• Low contrast
• Alignment
• Gantry tilt
• Distance
• Distance between slices

In addition to phantom image quality, IndoQCT has included several patient image quality parameters that can be tested, which include the following:

1. Patient CT number
2. Patient noise calculation (see Publication no. 6 and 7)
3. Patient low contrast
4. Patient alignment
5. Patient diameter

Additional Features

In addition to the main features, IndoQCT has additional features that are useful for activities other than quality control, which are as follows:

1. Multiple-windows blending in color domain (see Publication no. 6).
2. Images reformation in sagittal and coronal planes, with image interpolation
   and data slicing to oblique and irregular reconstructions.
3. Generation of computational phantoms with various designs and parameter
   settings (see Publications no. 8, 11, and 13).
4. Modification of DICOM images for educational and research purposes
   includes: move, flip, rotate, resize, crop, add noise and blur, DICOM
   anonymization, and modified DICOM storage.
5. Noise reduction with various options of algorithm (see Publications no. 4, 12,
   17, and 19).
6. Image comparison with various parameters, such as mean squared error
   (MSE), peak signal-to-noise ratio (PSNR), and structural similarity (SSIM).
7. Texture analysis in the first order, gray level co-occurrence matrix (GLCM),
   gray level run length matrix (GLRLM), and gray level size zone matrix
   (GLZM)

More Features

In order to provide convenience for users and practitioners, IndoQCT includes the following features:

1. Connection to the Picture Archiving and Communication System (PACS), to facilitate users in collecting images directly from the DICOM server.
2. Storage to an integrated local database that is useful for recording all measurements that have been made. This storage has been facilitated with an export tool to save data in Microsoft Excel document format (*.xlxs).
3. Analyze various measurements of image quality. This is useful for viewing measurement trends on a certain parameter according to what the user needs, both chronologically and analytically.
4. Generation of measurement reports in portable document file (PDF) format. This feature can help users to quickly and easily create measurement reports for documentation purposes.
5. Evaluation of image quality measurements based on standards. IndoQCT implements automatic evaluations based on standards set by nuclear regulatory agencies including Bapeten, IAEA, ACR, AAPM, as well as usercustomized ones that can be flexibly modified.
6. Sorting datasets with multiple sequence configurations that make it easy for users to sort mixed images in one folder.
7. Image annotation, ROI, and saving to common images to facilitate research publications and education.