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An estimation of a resected cancer lodge localization after breast tumor surgery is a challenging task during radiotherapy planning. Knowledge about the tumor lodge position and shape could improve the radiation dose distribution. However, the tumor no longer exists after the surgery, but information about its position is available in the 3D image acquired before the surgery. Therefore, image registration...
Localization of a resected tumor lodge after a breast cancer surgery is a challenging task for the radiotherapy planning. Currently, the problem is handled by creating radiation dose margins, which take into account the lack of information about lodge localization. We propose an alternative approach based on the image registration techniques, that aims to align computed tomography 3D images before...
The paper addresses a problem of feature selection for automatic prostate segmentation in Computed Tomography (CT) planning data for radiotherapy process. The following image descriptors have been tested in 2D and 3D scenarios: standard Hounsfield Unit (HU) profiles, histogram of oriented gradient (HoG), Haar wavelets, and Modality Independent Neighborhood Descriptor (MIND). The task was to distinguish...
In this paper we present a novel method of medical CT data segmentation using explicit atlas-type knowledge and Active Appearance Model (AAM) as a principal segmentation tool. New approach of automatic landmarks creation for AAM is proposed. Obtained results of automatic segmentation of prostate image in the CT scans are compared with true outlines drawn by medical doctors during the radiotherapy...
This paper addresses a problem of automatic segmentation of computed tomography (CT) data in context of prostate radiotherapy planning. A new 3D algorithm is proposed in which a prostate is automatically contoured in CT images. The proposed segmentation scenario consists of the following steps: 1) both CT and magnetic resonance (MR) data of a patient are acquired, 2) due to better visibility of soft...
Planning radiotherapy of prostate cancer requires the prostate segmentation in computed tomography (CT) images that can be manual (done by medical doctors), semi-automatic or automatic. Additional usage of magnetic resonance (MR) images, where the soft tissue are better visible, makes this operation more robust. The paper addresses the problem of prostate segmentation in MR data. Its main contribution...
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