Abstract
Automating the detection of lesions in liver CT scans requires a high performance and robust solution. With CT-scan start to become the norm in emergency department, the need for a fast and efficient liver lesions detection method is arising. In this paper, we propose a fast and evolvable method to profile the features of pre-segmented healthy liver and use it to detect the presence of liver lesions in emergency scenario. Our preliminary experiment with the MICCAI 2007 grand challenge datasets shows promising results of a fast training time, ability to evolve the produced healthy liver profiles, and accurate detection of the liver lesions. Lastly, the future work directions are also presented.
| Original language | English |
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| Title of host publication | 33rd Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS 2011 |
| Pages | 5169-5173 |
| Number of pages | 5 |
| DOIs | |
| Publication status | Published - 2011 |
| Externally published | Yes |
| Event | International Conference of the IEEE Engineering in Medicine and Biology Society 2011 - Boston, United States of America Duration: 30 Aug 2011 → 3 Sept 2011 Conference number: 33rd https://ieeexplore.ieee.org/xpl/conhome/6067544/proceeding (Proceedings) |
Publication series
| Name | Proceedings of the Annual International Conference of the IEEE Engineering in Medicine and Biology Society, EMBS |
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| ISSN (Print) | 1557-170X |
Conference
| Conference | International Conference of the IEEE Engineering in Medicine and Biology Society 2011 |
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| Abbreviated title | EMBC 2011 |
| Country/Territory | United States of America |
| City | Boston |
| Period | 30/08/11 → 3/09/11 |
| Internet address |