DLCExpert is Mirada’s first clinical application to utilize our next generation deep learning-based AI in Radiotherapy technology. DLCExpert delivers computer-drawn fully automated organ-at-risk contouring (Deep Learning Contouring or DLC for short). Utilizing Mirada’s most advanced learning algorithms and software optimizations, the truly Expert component of DLCExpert is that the software learns your contouring preferences and guidelines, using your own images and contours. DLCExpert really is Your Data, Your Contours!
LEARN MORE ABOUT DLCExpert™
Radiotherapy Imaging Workflow Management.
Learn more here: Efficient, Accurate, Agile
Radiotherapy Imaging Workflow Management.
Learn more here: Efficient, Accurate, Agile
Whether you are looking to enhance your workflow in a busy radiation therapy department, want to implement efficient adaptive therapy processes, or need superior accuracy in planning for proton therapy, we can help you with the transformation you require.
Our specialist team works with leading academic institutions to provide applications that address the most time-consuming clinical tasks. At the core of this are Mirada’s proven innovative algorithms such as the DLC (Deep Learning Contouring) and DIR (deformable image registration) algorithms.
Mirada’s radiation therapy imaging workstation, RTx™, and intelligent automation platform, Workflow Box™, are bringing automation and ease of use to the radiation therapy planning process.
Our software is vendor-neutral and can be configured to support your specific workflow.
“Mirada RTx has become an indispensable part of the treatment preparation workflow in our clinic. The software provides us with a ton of options for image registration and contouring, in a user-friendly environment which enables you to generate your own layouts and macros. Mirada employees are very communicative and helpful, offering support via online meetings when necessary. During live visits, they dive into our clinical workflows to be able to adapt the software to our specific needs.”
– Ellen Brunenberg, Department of Radiation Oncology, Radboudumc, Nijmegen, The Netherlands
