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INTDose is a software product intended to support the radiation therapy treatment planning process by providing independent dose verification through Monte Carlo simulation. INTDose is not a treatment planning system or a radiation delivery device and should only be used by trained radiation oncology personnel as a quality assurance tool.

INTDose is a software product used within a radiation therapy clinic for quality assurance and treatment plan verification. It allows clinicians to perform a second check of a radiotherapy dose generated by a treatment planning system by simulating the transport of ionizing radiation in patients using an independent Monte Carlo algorithm. INTDose is implemented such that one or more clients may communicate calculation requests to a central dose calculation server. While INTDose operates in the field of radiation therapy, it is neither a treatment planning system nor radiation delivery device. INTDose never comes into contact with patients and cannot control treatment delivery devices or any other medical devices. It is an analysis tool to be used only by trained radiation oncology personnel for quality assurance purposes.

INTContour provides a machine learning-based approach for the automatic segmentation of structures including treatment targets and organs at risk to support the radiation therapy treatment planning process. INTContour is intended as an initial method to segment and contour study series; therefore, this software must be used in conjunction with an appropriate software to edit the segmentation results if necessary. It is not intended to replace a thorough review by qualified medical professionals. INTContour is developed for use by dosimetrists, medical physicists, and radiation oncologists. The currently supported anatomical regions for automatic segmentation are head and neck, thorax, abdomen, and male pelvis.

INTContour is a software-only product that uses a machine learning-based approach to perform automatic segmentation of structures in medical images, coupled with tools for visualizing the segmentation results. A library of previously contoured expert cases serves as inputs to train the machine learning algorithms, specifically, convolutional networks (CNNs), to perform automatic segmentation. The results of the automatic segmentation will be stored in the DICOM Radiotherapy Structure Set (RTSTRUCT) format, which can be sent to desired destinations via the DICOM protocol. INTContour is intended to be used by dosimetrists, medical physicists, and radiation oncologists, and serves as an initial method to segment and contour study series. It must be used in conjunction with appropriate software to edit the segmentation results if necessary. The currently supported anatomical regions for automatic segmentation are head and neck, thorax, abdomen, and male pelvis. INTContour software is intended to be deployed within a hospital's private network on a workstation with an advanced graphics processing unit (GPU) and runs as a service. A web-based interface is used to access the service and manage the transfer of data, automatic segmentation, and visualization.