Fully automatic segmentation of the hippocampus in MR images

نویسندگان

  • G. Starck
  • M. Borga
  • M. Friberg
  • E. Olsson
  • S. Ribbelin
  • H. Knutsson
  • S. Ekholm
  • H. Malmgren
چکیده

Department of Radiation Physics, Göteborg University, Göteborg, SWEDEN, Department of Medical Physics and Biomedical Engineering, Sahlgrenska University Hospital, Göteborg, SWEDEN, Medical Informatics, Department of Biomedical Engineering, Linköping University, Linköping , SWEDEN, Department of Philosophy, Göteborg University, Göteborg, SWEDEN, Department of Radiology, Göteborg University, Göteborg, SWEDEN.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Method for Body Fat Composition Analysis in Abdominal Magnetic Resonance Images Via Self-Organizing Map Neural Network

Introduction: The present study aimed to suggest an unsupervised method for the segmentation of visceral adipose tissue (VAT) and subcutaneous adipose tissue (SAT) in axial magnetic resonance (MR) images of the abdomen. Materials and Methods: A self-organizing map (SOM) neural network was designed to segment the adipose tissue from other tissues in the MR images. The segmentation of SAT and VA...

متن کامل

Quantitative Comparison of SPM, FSL, and Brainsuite for Brain MR Image Segmentation

Background: Accurate brain tissue segmentation from magnetic resonance (MR) images is an important step in analysis of cerebral images. There are software packages which are used for brain segmentation. These packages usually contain a set of skull stripping, intensity non-uniformity (bias) correction and segmentation routines. Thus, assessment of the quality of the segmented gray matter (GM), ...

متن کامل

A multi-scale convolutional neural network for automatic cloud and cloud shadow detection from Gaofen-1 images

The reconstruction of the information contaminated by cloud and cloud shadow is an important step in pre-processing of high-resolution satellite images. The cloud and cloud shadow automatic segmentation could be the first step in the process of reconstructing the information contaminated by cloud and cloud shadow. This stage is a remarkable challenge due to the relatively inefficient performanc...

متن کامل

Comparison of state-of-the-art atlas-based bone segmentation approaches from brain MR images for MR-only radiation planning and PET/MR attenuation correction

Introduction: Magnetic Resonance (MR) imaging has emerged as a valuable tool in radiation treatment (RT) planning as well as Positron Emission Tomography (PET) imaging owing to its superior soft-tissue contrast. Due to the fact that there is no direct transformation from voxel intensity in MR images into electron density, itchr('39')s crucial to generate a pseudo-CT (Computed Tomography) image ...

متن کامل

An Automated MR Image Segmentation System Using Multi-layer Perceptron Neural Network

Background: Brain tissue segmentation for delineation of 3D anatomical structures from magnetic resonance (MR) images can be used for neuro-degenerative disorders, characterizing morphological differences between subjects based on volumetric analysis of gray matter (GM), white matter (WM) and cerebrospinal fluid (CSF), but only if the obtained segmentation results are correct. Due to image arti...

متن کامل

Object-Oriented Method for Automatic Extraction of Road from High Resolution Satellite Images

As the information carried in a high spatial resolution image is not represented by single pixels but by meaningful image objects, which include the association of multiple pixels and their mutual relations, the object based method has become one of the most commonly used strategies for the processing of high resolution imagery. This processing comprises two fundamental and critical steps towar...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2002