Howmedica Osteonics Corporation

Maximilien Mayya

Jean Chaoui

Sergii Poltaretskyi

Manuel Jean-Marie Urvoy

Charlotte Le Saint

A surgical planning system for use in surgical procedures to repair an anatomy of interest includes a preplanning system to generate a virtual surgical plan and a mixed reality system that includes a visualization device wearable by a user to view the virtual surgical plan projected in a real environment. The virtual surgical plan includes a 3D virtual model of the anatomy of interest. When wearing the visualization device, the user can align the 3D virtual model with the real anatomy of interest, thereby achieving a registration between details of the virtual surgical plan and the real anatomy of interest. The registration enables a surgeon to implement the virtual surgical plan on the real anatomy of interest without the use of tracking markers.

Soft tissue structure determination from CT images

Orthopedic surgical planning based on soft tissue and bone density modeling

Techniques and systems are described for planning shoulder stability enhancement surgeries. A computing system may determine a size of a predicted premorbid glenoid bone of the patient of a patient, a size of a Bankart lesion on a morbid glenoid bone of the patient, and a size of a geodesic surface on a 3-dimensional model of a predicted premorbid humerus of the patient. The geodesic surface is defined at least in part by a projected medial border of a Hill-Sachs lesion on a morbid humerus and a projected medial border of a footprint of a humeral head of the morbid humerus. The computing system may determine, based on the three areal sizes, whether bone loss of the patient involves joint engagement. The computing system may output an indication of whether a shoulder stability enhancement surgery that includes a bone graft is recommended for the patient.

Automated planning of shoulder stability enhancement surgeries

Techniques are described for determining a pre-morbid shape of an anatomical object. Processing circuitry may determine an aligned shape based on image data with under- or over-segmentation. The processing circuitry may utilize the aligned shape and a shape model such as a mean shape model of the anatomical object to register the aligned shape to the shape model and generate information indicative of the pre-morbid shape of the anatomical object.

Pre-morbid characterization of anatomical object using statistical shape modeling (SSM)

Techniques are described for closed surface fitting (CSF). Processing circuitry may determine a plurality of points on a shape, determine a contour, used to determine a shape of an anatomical object, from image information of one or more images of a patient, and determine corresponding points on the contour that correspond to the plurality of points on the shape based on at least one of respective normal vectors projected from points on the shape and normal vectors projected from points on the contour. The processing circuitry may generate a plurality of intermediate points between the points on the shape and the corresponding points on the contour, generate an intermediate shape based on plurality of intermediate points, and generate a mask used to determine the shape of the anatomical object based on the intermediate shape.

Closed surface fitting for segmentation of orthopedic medical image data

A system is configured to obtain image data of a joint of a patient; determine that the joint includes an existing implant; and one or both of generate an identification of a type for the existing implant and generate a pre-implant, morbid approximation of the joint.

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Brest, France

Maximilien Mayya