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- Publisher Website: 10.1118/1.597064
- Scopus: eid_2-s2.0-0027523034
- PMID: 8455515
- WOS: WOS:A1993KM73500009
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Article: Automatic segmentation of liver structure in ct images
Title | Automatic segmentation of liver structure in ct images |
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Authors | |
Keywords | abdominal imaging computed tomography computer vision computer-aided diagnosis liver organ transplant |
Issue Date | 1993 |
Citation | Medical Physics, 1993, v. 20, n. 1, p. 71-78 How to Cite? |
Abstract | The segmentation and three-dimensional representation of the liver from a computed tomography (CT) scan is an important step in many medical applications, such as in the surgical planning for a living-donor liver transplant and in the automatic detection and documentation of pathological states. A method is being developed to automatically extract liver structure from abdominal CT scans using a priori information about liver morphology and digital image-processing techniques. Segmentation is performed sequentially image-by-image (slice-by-slice), starting with a reference image in which the liver occupies almost the entire right half of the abdomen cross section. Image processing techniques include gray-level thresholding, Gaussian smoothing, and eight-point connectivity tracking. For each case, the shape, size, and pixel density distribution of the liver are recorded for each CT image and used in the processing of other CT images. Extracted boundaries of the liver are smoothed using mathematical morphology techniques and B-splines. Computer-determined boundaries were compared with those drawn by a radiologist. The boundary descriptions from the two methods were in agreement, and the calculated areas were within 10%. © 1993, American Association of Physicists in Medicine. All rights reserved. |
Persistent Identifier | http://hdl.handle.net/10722/315907 |
ISSN | 2021 Impact Factor: 4.506 2020 SCImago Journal Rankings: 1.473 |
ISI Accession Number ID |
DC Field | Value | Language |
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dc.contributor.author | Bae, Kyongtae T. | - |
dc.contributor.author | Giger, Maryellen L. | - |
dc.contributor.author | Chen, Chin Tu | - |
dc.contributor.author | Kahn, Charles E. | - |
dc.date.accessioned | 2022-08-24T15:48:33Z | - |
dc.date.available | 2022-08-24T15:48:33Z | - |
dc.date.issued | 1993 | - |
dc.identifier.citation | Medical Physics, 1993, v. 20, n. 1, p. 71-78 | - |
dc.identifier.issn | 0094-2405 | - |
dc.identifier.uri | http://hdl.handle.net/10722/315907 | - |
dc.description.abstract | The segmentation and three-dimensional representation of the liver from a computed tomography (CT) scan is an important step in many medical applications, such as in the surgical planning for a living-donor liver transplant and in the automatic detection and documentation of pathological states. A method is being developed to automatically extract liver structure from abdominal CT scans using a priori information about liver morphology and digital image-processing techniques. Segmentation is performed sequentially image-by-image (slice-by-slice), starting with a reference image in which the liver occupies almost the entire right half of the abdomen cross section. Image processing techniques include gray-level thresholding, Gaussian smoothing, and eight-point connectivity tracking. For each case, the shape, size, and pixel density distribution of the liver are recorded for each CT image and used in the processing of other CT images. Extracted boundaries of the liver are smoothed using mathematical morphology techniques and B-splines. Computer-determined boundaries were compared with those drawn by a radiologist. The boundary descriptions from the two methods were in agreement, and the calculated areas were within 10%. © 1993, American Association of Physicists in Medicine. All rights reserved. | - |
dc.language | eng | - |
dc.relation.ispartof | Medical Physics | - |
dc.subject | abdominal imaging | - |
dc.subject | computed tomography | - |
dc.subject | computer vision | - |
dc.subject | computer-aided diagnosis | - |
dc.subject | liver | - |
dc.subject | organ transplant | - |
dc.title | Automatic segmentation of liver structure in ct images | - |
dc.type | Article | - |
dc.description.nature | link_to_subscribed_fulltext | - |
dc.identifier.doi | 10.1118/1.597064 | - |
dc.identifier.pmid | 8455515 | - |
dc.identifier.scopus | eid_2-s2.0-0027523034 | - |
dc.identifier.volume | 20 | - |
dc.identifier.issue | 1 | - |
dc.identifier.spage | 71 | - |
dc.identifier.epage | 78 | - |
dc.identifier.isi | WOS:A1993KM73500009 | - |