Automatic Segmentation of Teeth from Dentomaxillofacial 3D-CT Images
نویسندگان
چکیده
منابع مشابه
Automatic Abdominal Organ Segmentation from CT images
In the recent years a great deal of research work has been devoted to the development of semi-automatic and automatic techniques for the analysis of abdominal CT images. Some of the current interests are the automatic diagnosis of liver, spleen, and kidney pathologies and the 3D volume rendering of the abdominal organs. The first and fundamental step in all these studies is the automatic organs...
متن کاملOrgan segmentation from 3D CT images
Publications: Method for automatically segmenting the spinal cord and canal from 3D CT images [6], Nyúl, László Gábor [7], Kanyó Judit [8], Máté Eörs [9], Makay Géza [10], Balogh Emese [11], Fidrich Márta [12], and Kuba Attila [13] , Computer Analysis of Images and Patterns, 2005, Berlin; Heidelberg, p.456 463, (2005) 3D segmentation of liver, kidneys and spleen from CT images [14], Bekes, Györ...
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Introduction: Various computer assisted medical procedures such as dental implant, orthodontic planning, face, jaw and cosmetic surgeries require automatic quantification and volumetric visualization of teeth. In this regard, segmentation is a major step. Material and Methods: In this paper, inspired by our previous experiences and considering the anatomical knowledge of teeth and jaws, we prop...
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Introduction: The purpose of this study was to develop a technique for automatic segmentation based on Fourier descriptors for separating smooth objects from the background in SPECT-images. The aim of the segmentation method was to be able to automatically outline kidneys in SPECT-images of patients undergoing radionuclide therapy with 177 Lu-DOTATATE. The potential advantage of combining SPECT...
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We present a method to address the challenging problem of segmentation of lumbar vertebrae from CT images acquired with varying fields of view. Our method is based on cascaded 3D Fully Convolutional Networks (FCNs) consisting of a localization FCN and a segmentation FCN. More specifically, in the first step we train a regression 3D FCN (we call it “LocalizationNet”) to find the bounding box of ...
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ژورنال
عنوان ژورنال: Japanese Journal of Radiological Technology
سال: 2010
ISSN: 0369-4305,1881-4883
DOI: 10.6009/jjrt.66.343