UNDIP, Semarang (January 10, 2026) – At the beginning of 2026, Universitas Diponegoro (UNDIP) has produced “IndoQCT v26d: Software for Evaluating the Quality of Computed Tomography Images,” the latest software developed to support the automatic, objective, and efficient evaluation of CT image quality. The official launch of IndoQCT v26d will be held on Saturday, January 10, 2026, from 09:00 to 11:00 WIB, and will be broadcast on the official YouTube channel of UNDIP Physics, which will also feature an explanation of the software.
This innovation is expected to serve as a supporting tool for medical physicists in performing CT-scan quality control more quickly and effectively, as well as a research tool in the field of CT imaging and an educational support medium for medical physics and radiology. In the healthcare sector, this technology also helps reduce the risks associated with CT-scan procedures for patients.
IndoQCT v26d represents the latest development version of CT image quality evaluation software that has been under development since 2018. This version introduces several new flagship features to support both research and clinical Quality Control (QC) needs, including Detectability Index Measurements for assessing object detectability, integrated storage of DICOM information into a centralized database, as well as various other feature enhancements.
UNDIP has successfully collaborated with PT Quarta Medika Indonesia (QMI), enabling this leading innovation—resulting from research conducted by UNDIP Medical Physics lecturers led by Dr. Choirul Anam and Prof. Heri Sutanto, together with their team including Ariij Naufal and Wahyu S. Budi—to reach the commercialization stage.
This is the fourth version of the software. Previous versions included v22a, followed by v24b, v25c, and the current v26d. In this release, IndoQCT has been equipped with several advanced features, including detectability index measurements using the NPW and NPWE models; human observer analysis employing AFC, ROC, and LROC methods; storage of DICOM information into an integrated database; as well as numerous bug fixes and system improvements. The user interface of IndoQCT v26d has also been refreshed, offering a more modern, colorful, and user-friendly appearance. The input parameter tabs, which were previously static, have now been redesigned to be more dynamic, and file management features have been significantly updated.
To date, approximately 95 scientific papers have been published as outcomes of IndoQCT development. Several of these papers have appeared in leading journals in the field of medical physics, such as Medical Physics (Med Phys), Physics in Medicine and Biology (Phys Med Biol), Journal of Applied Clinical Medical Physics (J Appl Clin Med Phys), Physica Medica (Phys Med), Radiation Physics and Chemistry (Rad Phys Chem), Biomedical Physics and Engineering Express (Biomed Phys Eng), Journal of Medical Physics (J Med Phys), and others. To date, IndoQCT has been downloaded and utilized by users in more than 90 countries worldwide.
IndoQCT was developed to address various challenges in conventional CT Quality Control (QC) procedures, which are still largely performed manually, require considerable time—particularly for daily checks—and are susceptible to examiner subjectivity bias. With IndoQCT, CT image quality evaluation can be performed automatically and in a standardized manner, significantly improving efficiency and objectivity.
Compared to similar software, IndoQCT offers several key advantages, including support for a wide range of phantoms without dependence on specific vendors, as well as efficient, objective, universal, and portable automated measurements. In addition, IndoQCT enables direct measurement of image quality metrics from clinical patient images, thereby facilitating dose optimization in a more practical and objective manner.
Additional features of IndoQCT include texture analysis, noise reduction, multiple image window options, including RGB multi-window blending, as well as advanced image reformatting capabilities (sagittal, coronal, oblique, and irregular planes). All image quality parameters are stored in an integrated database, and PDF reports can be generated automatically.
From a development perspective, IndoQCT was initially developed using MATLAB starting in 2018 and was later redeveloped in the Python programming language in 2021 to facilitate broader distribution and further development.
This innovation by UNDIP researchers demonstrates that Universitas Diponegoro has successfully produced medical technologies that provide direct benefits to the wider community.
Source: https://undip.ac.id