Howmedica Osteonics Corporation

Manuel Jean-Marie Urvoy

Jean Chaoui

Sergii Poltaretskyi

Damien Cariou

Maximilien Mayya

Vincent Abel Maurice Simoes

Charlotte Le Saint

Marie-Charlotte Desseroit

Florence Delphine Muriel MaillÉ

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

A computing system generates a plurality of training datasets from past shoulder surgery cases and uses the plurality of training datasets to train a neural network. Each output layer neuron in a plurality of output layer neurons of the neural network corresponds to a different class in one or more shoulder pathology classification systems. The computing system may obtain a current input vector that corresponds to a current patient. Additionally, the computing system may apply the neural network to the current input vector to generate a current output vector. The computing system may determine, based on the current output vector, a recommended type of shoulder surgery for the current patient.

Neural network for recommendation of shoulder surgery type

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

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Brest, France

Manuel Jean-Marie Urvoy