Publication detail
Data processing in studying the temporomandibular joint, using MR imaging and sonographic techniques
SMÉKAL, Z. LIBERDA, O. BARTUŠEK, K. MIKULKA, J.
Original Title
Data processing in studying the temporomandibular joint, using MR imaging and sonographic techniques
English Title
Data processing in studying the temporomandibular joint, using MR imaging and sonographic techniques
Type
conference paper
Language
en
Original Abstract
The temporomandibular joint is one of the most complicated joints in the human body. Diagnosing its disorders is difficult because the pain is mistakenly taken for toothache, pain in the jaw bones, etc. The paper deals with a post-processing tomographic examination of temporomandibular joint. An interesting post-processing method was used to increase the contrast related to relaxation time T2. Both increasing the contrast and enhancing the arthritic region were realized by processing two MR images in different echo-times. The enhancement rate is realized on the basis of subjective MR image evaluation by the surgeon. Magnetic resonance images (MRIs) are of very low resolution and contrast. An appropriate algorithm has been found, which consists of preprocessing the image by a smoothing filter, focusing, and four-phase level set segmentation. This method segments the image on the basis of the intensity of respective regions and is thus suitable to be applied to the above MR images, in which no sharp edges occur.
English abstract
The temporomandibular joint is one of the most complicated joints in the human body. Diagnosing its disorders is difficult because the pain is mistakenly taken for toothache, pain in the jaw bones, etc. The paper deals with a post-processing tomographic examination of temporomandibular joint. An interesting post-processing method was used to increase the contrast related to relaxation time T2. Both increasing the contrast and enhancing the arthritic region were realized by processing two MR images in different echo-times. The enhancement rate is realized on the basis of subjective MR image evaluation by the surgeon. Magnetic resonance images (MRIs) are of very low resolution and contrast. An appropriate algorithm has been found, which consists of preprocessing the image by a smoothing filter, focusing, and four-phase level set segmentation. This method segments the image on the basis of the intensity of respective regions and is thus suitable to be applied to the above MR images, in which no sharp edges occur.
Keywords
MRI, sonography, temporomandibular joint, wavelet transform, image segmentation
RIV year
2009
Released
06.07.2009
Location
Santorini, Greece
ISBN
978-1-4244-3298-1
Book
16th International Conference on Digital Signal Processing (DSP 2009)
Pages from
100
Pages to
106
Pages count
6
URL
BibTex
@inproceedings{BUT31017,
author="Zdeněk {Smékal} and Ondřej {Liberda} and Karel {Bartušek} and Jan {Mikulka}",
title="Data processing in studying the temporomandibular joint, using MR imaging and sonographic techniques",
annote="The temporomandibular joint is one of the most complicated
joints in the human body. Diagnosing its disorders is
difficult because the pain is mistakenly taken for toothache,
pain in the jaw bones, etc.
The paper deals with a post-processing tomographic
examination of temporomandibular joint. An interesting
post-processing method was used to increase the contrast
related to relaxation time T2. Both increasing the contrast
and enhancing the arthritic region were realized by
processing two MR images in different echo-times. The
enhancement rate is realized on the basis of subjective MR
image evaluation by the surgeon. Magnetic resonance
images (MRIs) are of very low resolution and contrast. An
appropriate algorithm has been found, which consists of preprocessing
the image by a smoothing filter, focusing, and
four-phase level set segmentation. This method segments
the image on the basis of the intensity of respective regions
and is thus suitable to be applied to the above MR images,
in which no sharp edges occur.",
booktitle="16th International Conference on Digital Signal Processing (DSP 2009)",
chapter="31017",
howpublished="electronic, physical medium",
year="2009",
month="july",
pages="100--106",
type="conference paper"
}