Skip to Main content Skip to Navigation
Journal articles

DENTALMAPS: Automatic Dental Delineation for Radiotherapy Planning in Head and Neck Cancer

Abstract : Purpose To propose an automatic atlas-based segmentation framework of the dental structures, called Dentalmaps, and to assess its accuracy and relevance to guide dental care in the context of intensity-modulated radiotherapy. Methods and Materials A multi-atlas-based segmentation, less sensitive to artifacts than previously published head-and-neck segmentation methods, was used. The manual segmentations of a 21-patient database were first deformed onto the query using nonlinear registrations with the training images and then fused to estimate the consensus segmentation of the query. Results The framework was evaluated with a leave-one-out protocol. The maximum doses estimated using manual contours were considered as ground truth and compared with the maximum doses estimated using automatic contours. The dose estimation error was within 2-Gy accuracy in 75% of cases (with a median of 0.9 Gy), whereas it was within 2-Gy accuracy in 30% of cases only with the visual estimation method without any contour, which is the routine practice procedure. Conclusions Dose estimates using this framework were more accurate than visual estimates without dental contour. Dentalmaps represents a useful documentation and communication tool between radiation oncologists and dentists in routine practice. Prospective multicenter assessment is underway on patients extrinsic to the database.
Complete list of metadatas

https://hal.inria.fr/inria-00616186
Contributor : Project-Team Asclepios <>
Submitted on : Friday, August 19, 2011 - 7:47:28 PM
Last modification on : Thursday, June 11, 2020 - 3:06:32 AM

Identifiers

  • HAL Id : inria-00616186, version 1

Collections

Citation

Juliette Thariat, Liliane Ramus, Philippe Maingon, Guillaume Odin, Vincent Grégoire, et al.. DENTALMAPS: Automatic Dental Delineation for Radiotherapy Planning in Head and Neck Cancer. International Journal of Radiation Oncology - Biology - Physics, Elsevier, 2011, 82 (5), pp.1858-1865. ⟨inria-00616186⟩

Share

Metrics

Record views

594