Raysearch Laboratories Ab (publ)

Raysearch Laboratories Ab

Stina Svensson

Kjell Eriksson

Ola Weistrand

Sebastian Andersson

A deep learning model may be trained to provide an estimated image of the interior of a patient, based on a number of image sets, each image set comprising an interior image of the interior of a person and a contour image of the person's outer contour at a specific point in time. The model is trained to establish an optimized parametrized conversion function G specifying the correlation between the interior of the person and the persons outer contour based on the image sets. The conversion function G can then be used to provide estimated images of patient's interior based on their contours.

System and method for training a machine learning model and for providing an estimated interior image of a patient

A computer based method of obtaining a 3D image of a part of a patient's body is disclosed, based on a fraction image having a limited field-of-view and extending the field of view with information from an image of the patient's outline, obtained from a surface scan of the patient. Anatomical data from the planning image are preferably used to fill in the outline image, by means of a contour-guided deformable registration between the planning image and contour.

System and method for providing an extended image of a patient

A method of obtaining a 3D image of a part of a patient's body is disclosed, based on a fraction image having a limited field-of-view and complementing this with information from a planning image having a greater field-of-view. In the area outside of the fraction image field-of-view, contour and anatomical data from the planning image are used to complement the fraction image, by means of a contour-guided deformable registration between the planning image and the fraction image.

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Stockholm, Sweden

Stina Svensson