# US 10,482,602 B2 · System and method for image segmentation > Agents: this data is available as JSON from the patentgrep API and MCP server — see https://patentgrep.com/llms.txt - Number: US 10,482,602 B2 - Document ID: US10482602B2 - Status: Granted - Kind: B2 - Application number: 16/403,709 - Filed: 2019-05-06 - Published: 2019-08-22 - Granted: 2019-11-19 - Earliest claimed: 2015-05-05 - Assignees: Shanghai United Imaging Healthcare Co., Ltd. - Applicants: Shanghai United Imaging Healthcare Co., Ltd. - Inventors: Lilong Wang; Lijia Wang; Yufei Mao; Xiaolin Meng; Xiaodong Wang; Cheng Li - Web page: https://patentgrep.com/patent/US10482602B2 ## CPC - G06T 7/11: Region-based segmentation - G06T 7/136: involving thresholding - G06T 7/143: involving probabilistic approaches, e.g. Markov random field [MRF] modelling - G06T 7/155: involving morphological operators - G06T 7/187: involving region growing; involving region merging; involving connected component labelling - G06T 2200/04: involving 3D image data - G06T 2207/10072: Tomographic images - G06T 2207/20156: Automatic seed setting - G06T 2207/20161: Level set - G06T 2207/30061: Lung - G06T: IMAGE DATA PROCESSING OR GENERATION, IN GENERAL ## Abstract A system and method for image segmentation are provided. A three-dimensional image data set representative of a region including at least one airway may be acquired. The data set may include a plurality of voxels. A first-level seed within the region may be identified. A first-level airway within the region may be identified based on the first-level seed. A second-level airway may be identified within the region based on the first-level airway. The first-level airway and the second-level airway may be fused to form an airway tree. ## Claims ### Claim 1 A method of image processing implemented on at least one machine, each of which has at least one processor and at least one storage device, the method comprising: acquiring a three-dimensional image data set representative of a region including at least one airway, the data set comprising a plurality of voxels; identifying a first-level seed within the region; identifying a first-level airway within the region based on the first-level seed; identifying a second-level airway within the region based on the first-level airway, wherein the identifying a second-level airway includes: defining a second-level seed based on the first-level airway; identifying a voxel set based on a level set method and the second-level seed; and selecting a voxel from the voxel set; determining a second characteristic value of the voxel, wherein the second characteristic value includes an energy function value; and marking, when the second characteristic value of the voxel is below a fourth threshold, the voxel as part of the second-level airway; and fusing the first-level airway and the second-level airway to form an airway tree. ### Claim 2 (depends on 1) The method of claim 1, the identifying a first-level airway comprising: selecting, from the plurality of voxels, an adjacent voxel of the first-level seed and neighboring voxels of the adjacent voxel; determining a characteristic value for the adjacent voxel and a characteristic value for each of the neighboring voxels; calculating a difference between the characteristic value for the adjacent voxel and the characteristic value for each of the neighboring voxels; and marking, when the characteristic value of the adjacent voxel is below a first threshold and when, for each of the neighboring voxels, the difference is below a second threshold, the adjacent voxel as part of the first-level airway. ### Claim 3 (depends on 1) The method of claim 1, the identifying a first-level airway comprising using a morphology based method. ### Claim 4 (depends on 1) The method of claim 1, the identifying a first-level airway comprising: determining a voxel set based on a level set method; selecting a voxel from the voxel set; determining a first characteristic value of the voxel, wherein the first characteristic value includes a grey level; and marking, when the first characteristic value of the voxel is below a third threshold, the voxel as part of the first-level airway. ### Claim 5 (depends on 1) The method of claim 1, wherein the first-level airway includes a low-level bronchus of a lung region, and the second-level airway includes a terminal bronchiole of a lung region. ### Claim 6 (depends on 1) The method of claim 1 further comprising: identifying a lung organ; identifying a lung tissue based on the fused airway and the lung organ; and labelling, based on the fused airway, the identified lung tissue as a left lung tissue or a right lung tissue. ### Claim 7 (depends on 6) The method of claim 6, further comprising: obtaining an image for a 2D layer of the lung organ; smoothing the image based on a morphology based method; and labelling a left lung portion of the lung organ including the second-level airway or a right lung portion of the lung organ including the second-level airway based on the smoothed image and the first-level airway. ### Claim 8 (depends on 6) The method of claim 6, the identifying a lung organ comprising: determining a lung region based on the plurality of voxels; removing a background based on the determined lung region; determining a 2D layer based on area of the 2D layer; and performing 3D region growing based on the 2D layer. ### Claim 9 (depends on 8) The method of claim 8, the determining a lung region comprising: selecting, from the plurality of voxels, a voxel; and determining, based on a comparison between a characteristic value of the voxel and a seventh threshold, whether the voxel belongs to the lung region. ### Claim 10 (depends on 8) The method of claim 8, the removing a background comprising: identifying a background send near an edge of the lung region; and performing region growing based on the background seed. ### Claim 11 A system comprising: at least one processor, and executable instructions that, when executed by the at least one processor, cause the at least one processor to effectuate a method comprising: acquiring a three-dimensional image data set representative of a region including at least one airway, the data set comprising a plurality of voxels; identifying a first-level seed within the region; identifying a first-level airway within the region based on the first-level seed; identifying a second-level airway within the region based on the first-level airway, wherein the identifying a second-level airway includes: defining a second-level seed based on the first-level airway; identifying a voxel set based on a level set method and the second-level seed; and selecting a voxel from the voxel set; determining a second characteristic value of the voxel, wherein the second characteristic value includes an energy function value; and marking, when the second characteristic value of the voxel is below a fourth threshold, the voxel as part of the second-level airway; and fusing the first-level airway and the second-level airway to form an airway tree. ### Claim 12 (depends on 11) The system of claim 11, the identifying a first-level airway comprising: selecting, from the plurality of voxels, an adjacent voxel of the first-level seed and neighboring voxels of the adjacent voxel; determining a characteristic value for the adjacent voxel and a characteristic value for each of the neighboring voxels; calculating a difference between the characteristic value for the adjacent voxel and the characteristic value for each of the neighboring voxels; and marking, when the characteristic value of the adjacent voxel is below a first threshold and when, for each of the neighboring voxels, the difference is below a second threshold, the adjacent voxel as part of the first-level airway. ### Claim 13 (depends on 11) The system of claim 11, the identifying a first-level airway comprising: determining a voxel set based on a level set method; selecting a voxel from the voxel set; determining a first characteristic value of the voxel, wherein the first characteristic value includes a grey level; and marking, when the first characteristic value of the voxel is below a third threshold, the voxel as part of the first-level airway. ### Claim 14 (depends on 11) The system of claim 11, wherein the first-level airway includes a low-level bronchus of a lung region, and the second-level airway includes a terminal bronchiole of a lung region. ### Claim 15 (depends on 11) The system of claim 11, further comprising: identifying a lung organ; identifying a lung tissue based on the fused airway and the lung organ; and labelling, based on the fused airway, the identified lung tissue as a left lung tissue or a right lung tissue. ### Claim 16 (depends on 15) The system of claim 15, further comprising: obtaining an image for a 2D layer of the lung organ; smoothing the image based on a morphology based method; and labelling a left lung portion of the lung organ including the second-level airway or a right lung portion of the lung organ including the second-level airway based on the smoothed image and the first-level airway. ### Claim 17 (depends on 15) The system of claim 15, the identifying a lung organ comprising: determining a lung region based on the plurality of voxels; removing a background based on the determined lung region; determining a 2D layer based on area of the 2D layer; and performing 3D region growing based on the 2D layer. ### Claim 18 (depends on 17) The system of claim 17, the determining a lung region comprising: selecting, from the plurality of voxels, a voxel; and determining, based on a comparison between a characteristic value of the voxel and a seventh threshold, whether the voxel belongs to the lung region. ### Claim 19 (depends on 17) The system of claim 17, the removing a background comprising: identifying a background send near an edge of the lung region; and performing region growing based on the background seed. ### Claim 20 A non-transitory computer readable medium comprising executable instructions that, when executed by at least one processor, cause the at least one processor to effectuate a method comprising: acquiring a three-dimensional image data set representative of a region including at least one airway, the data set comprising a plurality of voxels; identifying a first-level seed within the region; identifying a first-level airway within the region based on the first-level seed; identifying a second-level airway within the region based on the first-level airway, wherein the identifying a second-level airway includes: defining a second-level seed based on the first-level airway; identifying a voxel set based on a level set method and the second-level seed; and selecting a voxel from the voxel set; determining a second characteristic value of the voxel, wherein the second characteristic value includes an energy function value; and marking, when the second characteristic value of the voxel is below a fourth threshold, the voxel as part of the second-level airway; and fusing the first-level airway and the second-level airway to form an airway tree.