# US 10,482,606 B2 · Medical image reporting system and method > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,482,606 B2 - Document ID: US10482606B2 - Status: Granted - Kind: B2 - Application number: 15/596,553 - Filed: 2017-05-16 - Published: 2017-11-30 - Granted: 2019-11-19 - Earliest claimed: 2008-02-14 - Assignees: The Penn State Research Foundation - Applicants: The Penn State Research Foundation - Inventors: William E. Higgins; Jason D. Gibbs; Kun-Chang Yu; Michael W. Graham; Kongkuo Lu - Web page: https://patentgrep.com/patent/US10482606B2 ## CPC - G06T 7/162: involving graph-based methods - G06T 7/12: Edge-based segmentation - G06T 2207/20044: Skeletonization; Medial axis transform - G06T 2207/30061: Lung - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract This invention relates generally to medical imaging and, in particular, to a method and system for automatic lymph node station mapping, automatic path or route report generation. A computer-based system for automatically locating the central chest lymph-node stations in a 3D MDCT image is described. Automated analysis methods extract the airway tree, airway-tree centerlines, aorta, pulmonary artery, lungs, key skeletal structures, and major-airway labels. Geometrical and anatomical cues arising from the extracted structures are used to localize the major nodal stations. The system calculates and displays the nodal stations in 3D. Visualization tools within the system enable the user to interact with the stations to locate visible lymph nodes. ## Claims ### Claim 1 A method for automatically identifying at least one lymph node station in a thoracic region of a patient, said method comprising the steps of: calculating a 3D model of at least one anatomical structure in the chest based on 3D image data; calculating at least one anatomical cue derived from said at least one anatomical structure; and calculating at least one lymph node station based on said 3D image data and using said at least one anatomical cue wherein said calculating at least one lymph node station is performed automatically, the calculating step comprising automatically computing a plurality of Mountain Stations based on said 3D image data and automatically computing which of said Mountain Stations are accessible via a bronchoscope. ### Claim 2 (depends on 1) The method of claim 1 further comprising displaying said at least one lymph node station in a view. ### Claim 3 (depends on 1) The method of claim 1 wherein said anatomical structure comprise at least one of the patient's airway tree, aorta, pulmonary artery, lungs, vertebrae, and sternum from the image data. ### Claim 4 (depends on 3) The method of claim 3 wherein said anatomical structure comprise the airway tree, and said method further comprising calculating centerlines through the airways of the airway tree. ### Claim 5 (depends on 4) The method of claim 4 further comprising labeling individual airways of the airway tree. ### Claim 6 (depends on 1) The method of claim 1 wherein said calculating the at least one lymph node station is performed entirely automatically. ### Claim 7 (depends on 1) The method of claim 1 further comprising accepting input regarding a lymph node of the station. ### Claim 8 (depends on 7) The method of claim 7 further comprising calculating the lymph node within the station based on said input. ### Claim 9 (depends on 8) The method of claim 8 further comprising displaying said lymph node. ### Claim 10 (depends on 5) The method of claim 5 wherein said lymph node station is station M7, and said anatomical cues comprise a main carina, an inferior limit of a bronchus intermedius, a right limit of the right main bronchus, and left limit of the left main bronchus. ### Claim 11 (depends on 2) The method of claim 2 comprising displaying said station in a 3D view and a 2D multiplanar formatted image section. ### Claim 12 (depends on 1) The method of claim 1 comprising adjusting the anatomical cues. ### Claim 13 (depends on 2) The method of claim 2 comprising adjusting the view of the station. ### Claim 14 (depends on 1) The method of claim 1 further comprising calculating at least 10 Mountain Stations. ### Claim 15 A computing system for calculating at least one lymph node station based on 3D image data of a patient's thoracic region, said system comprising: a memory storing said image data; a processor in communication with said memory, the processor being operative to: a) calculate a 3D model of at least one anatomical structure in the chest of the patient based on said 3D image data; b) calculate at least one anatomical cue derived from said at least one anatomical structure; and c) calculate said at least one lymph node station based on said 3D image data and at least one anatomical cue, the calculating comprising automatically computing a plurality of Mountain Stations based, on said 3D image data and automatically computing which of said Mountain Stations are accessible via a bronchoscope. ### Claim 16 (depends on 15) The system of claim 15 further comprising a node tool to accept input regarding a lymph node within said lymph node station, and said processor being operative to calculate said lymph node in 3D. ### Claim 17 (depends on 15) The system of claim 15 further comprising a cue tool to adjust said at least one anatomical cue. ### Claim 18 (depends on 15) The system of claim 15 comprising a display and a display tool to adjust the view of the station. ### Claim 19 A method for automatically identifying at least one lymph node station in a thoracic region of a patient, said method comprising the steps of: calculating a 3D model of at least one anatomical structure in the chest based on 3D image data, the at least one anatomical structure including No-Fly zones being regions which should not be punctured; calculating at least one anatomical cue derived from said at least one anatomical structure; and calculating at least one lymph node station based on said 3D image data and using said at least one anatomical cue wherein said calculating at least one lymph node station is performed automatically, the calculating step comprising automatically computing a plurality of Mountain Stations based on the 3D image data and automatically computing which of said Mountain Stations are accessible, and thereby avoiding the No-Fly zones.