Siemens Aktiengesellschaft

Siemens Medical Solutions Usa, Inc.

Shaolei Feng

Shaohua Kevin Zhou

Rainer Graumann

Wei Zhang

Berthold Kiefer

Gerhard Kleinszig

Jingdan Zhang

Jin-hyeong Park

Andre De Oliveira

The pose of an implant represented in a medical image is determined from the medical image. The x-ray image of the implant is compared to a database of the implant viewed at different poses (e.g., viewed from different directions). The implant pose associated with the best match indicates the pose of the implant in the x-ray image.

Implant pose determination in medical imaging

A method and system for automatic lung segmentation in magnetic resonance imaging (MRI) images and videos is disclosed. A plurality of predetermined key landmarks of a lung are detected in an MRI image. The key landmarks may be detected using discriminative joint contexts representing combinations of multiple key landmarks. A lung boundary is segmented in the MRI image based on the detected key landmarks. The landmark detection and the lung boundary segmentation can be repeated in each frame of an MRI video.

Method and system for automatic lung segmentation in magnetic resonance imaging videos

Automated detection of structure is provided in ultrasound M-mode imaging. A coarse and fine search for structure is used. For example, a less noise susceptible initial position or range of positions for a given structure is determined. This position is then refined. The coarse positioning and/or the refined position may use machine-trained classifiers. The positions of other structure may be used in either coarse or fine positioning, such as using a Markov Random Field. The structure or structures may be identified in the M-mode image without user input of a location in the M-mode image or along the line.

Detection of structure in ultrasound M-mode imaging

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Plainsboro, NJ, United States of America

Shaolei Feng