Visualizing human brain surface from T1-weighted MR images using texture-mapped triangle meshes.

نویسندگان

  • Mika Seppä
  • Matti Hämäläinen
چکیده

We describe a novel method for visualizing brain surface from anatomical magnetic resonance images (MRIs). The method utilizes standard 2D texture mapping capabilities of OpenGL graphics language. It combines the benefits of volume rendering and triangle-mesh rendering, allowing fast and realistic-looking brain surface visualizations. Consequently, relatively low-resolution triangle meshes can be used while the texture images provide the necessary details. The mapping is optimized to provide good texture-image resolution for the triangles with respect to their original sizes in the 3D MRI volume. The actual 2D texture images are generated by depth integration from the original MRI data. Our method adapts to anisotropic voxel sizes without any need to interpolate the volume data into cubic voxels, and it is very well suited for visualizing brain anatomy from standard T(1)-weighted MR images. Furthermore, other OpenGL objects and techniques can be easily combined, for example, to use cut planes, to show other surfaces and objects, and to visualize functional data in addition to the anatomical information.

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

Measurement of the correlation coefficients between extracted features from CT and MR images

Introduction: Nowadays applying computer in image processing is being improved revolutionary for solving medical images deficiencies. Image features that are analysis in image processing show image information. The aim of the present study was to find correlation between CT- scan and MRI images' features. Materials and Methods: After data acquisition, applying...

متن کامل

Hypoxic-ischemic encephalopathy: diagnostic value of conventional MR imaging pulse sequences in term-born neonates.

PURPOSE To retrospectively compare different magnetic resonance (MR) imaging techniques and pulse sequences for the depiction of brain injury in neonatal hypoxic-ischemic encephalopathy. MATERIALS AND METHODS The institutional review board approved this retrospective study and waived informed consent. Term-born neonates underwent MR imaging within 10 days after birth because of perinatal asph...

متن کامل

Fully automatic segmentation of the brain from T1-weighted MRI using Bridge Burner algorithm.

PURPOSE To validate Bridge Burner, a new brain segmentation algorithm based on thresholding, connectivity, surface detection, and a new operator of constrained growing. MATERIALS AND METHODS T1-weighted MR images were selected at random from three previous neuroimaging studies to represent a spectrum of system manufacturers, pulse sequences, subject ages, genders, and neurological conditions....

متن کامل

Content Based Image Retrieval of Brain MR Images across Different Classes

Magnetic Resonance Imaging play a vital role in the decision-diagnosis process of brain MR images. For an accurate diagnosis of brain related problems, the experts mostly compares both T1 and T2 weighted images as the information presented in these two images are complementary. In this paper, rotational and translational invariant form of Local binary Pattern (LBP) with additional gray scale in...

متن کامل

Texture analysis of T1- and T2-weighted MR images and use of probabilistic neural network to discriminate posterior fossa tumours in children

Brain tumours are the most common solid tumours in children, representing 20% of all cancers. The most frequent posterior fossa tumours are medulloblastomas, pilocytic astrocytomas and ependymomas. Texture analysis (TA) of MR images can be used to support the diagnosis of these tumours by providing additional quantitative information. MaZda software was used to perform TA on T1 - and T2 -weight...

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:
  • NeuroImage

دوره 26 1  شماره 

صفحات  -

تاریخ انتشار 2005