13 research outputs found
Segmentation of Pelvic Organs at Risk Using Superpixels and Graph Diffusion in Prostate Radiotherapy
International audienc
Définition du volume cible anatomoclinique pour l’irradiation des cancers de l’œsophage
International audienc
Segmentation of organs at risk using superpixels on MRI or CT images in prostate radiotherapy
International audienc
Segmentation of Pelvic Organs at Risk Using Superpixels and Graph Diffusion in Prostate Radiotherapy
International audienc
PO-0971: Segmentation of organs at risk using superpixels on MRI or CT images in prostate radiotherapy
La radiothérapie assistée par l’imagerie nucléaire : les volumes cibles
International audienc
422 Value of adjuvant radiotherapy in prostate cancer pT2 with positive margins and postoperative PSA below 0.2 ng/ml
FDG-PET imaging for radiotherapy target volume definition in lung cancer
International audienc
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.
International audienceA segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake
Segmentation of heterogeneous or small FDG PET positive tissue based on a 3D-locally adaptive random walk algorithm.
International audienceA segmentation algorithm based on the random walk (RW) method, called 3D-LARW, has been developed to delineate small tumors or tumors with a heterogeneous distribution of FDG on PET images. Based on the original algorithm of RW [1], we propose an improved approach using new parameters depending on the Euclidean distance between two adjacent voxels instead of a fixed one and integrating probability densities of labels into the system of linear equations used in the RW. These improvements were evaluated and compared with the original RW method, a thresholding with a fixed value (40% of the maximum in the lesion), an adaptive thresholding algorithm on uniform spheres filled with FDG and FLAB method, on simulated heterogeneous spheres and on clinical data (14 patients). On these three different data, 3D-LARW has shown better segmentation results than the original RW algorithm and the three other methods. As expected, these improvements are more pronounced for the segmentation of small or tumors having heterogeneous FDG uptake