Development and evaluation of an automatic tumor segmentation tool: a comparison between automatic, semi-automatic and manual segmentation of mandibular odontogenic cysts and tumors
| Autor: | Maximilian E. H. Wagner, Majeed Rana, Daniel Modrow, Christopher H.K. Chui, Nils-Claudius Gellrich, Madiha Rana, Jens Keuchel |
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| Rok vydání: | 2014 |
| Předmět: |
medicine.medical_specialty
Time Factors medicine.medical_treatment Odontogenic Tumors Imaging Three-Dimensional Image Processing Computer-Assisted Medicine Humans Segmentation Mandibular Diseases Computer-assisted surgery business.industry Reproducibility of Results Pattern recognition Usability Magnetic Resonance Imaging Odontogenic Surgery Otorhinolaryngology Surgery Computer-Assisted Odontogenic Cysts Manual segmentation Tumor surgery Artificial intelligence Semi automatic Oral Surgery business Tomography X-Ray Computed Tumor segmentation |
| Zdroj: | Journal of cranio-maxillo-facial surgery : official publication of the European Association for Cranio-Maxillo-Facial Surgery. 43(3) |
| ISSN: | 1878-4119 |
| Popis: | Introduction In the treatment of cancer in the head and neck region, computer-assisted surgery can be used to estimate location and extent by segmentation of the tumor. This article presents a new tool (Smartbrush), which allows for faster automated segmentation of the tumor. Methods This new method was compared with other well-known techniques of segmentation. Thirty-eight patients with keratocystic odontogenic tumors were included in this study. The tumors were segmented using manual segmentation, threshold-based segmentation and segmentation using Smartbrush. All three methods were compared concerning usability, time expenditure and accuracy. Results The results suggest that segmentation using Smartbrush is significantly faster with comparable accuracy. Conclusions After a period of adjustment to the program, one can comfortably get reliable results that, compared with other methods, are not as dependent on the user's experience. Smartbrush segmentation is a reliable and fast method of segmentation in tumor surgery. |
| Databáze: | OpenAIRE |
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