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영상보간법을 이용한 디지털 치근단 방사선영상의 개선에 관한 연구
A Study on the Improvement of Digital Periapical Images using Image Interpolation Methods

치과방사선 1998년 28권 2호 p.387 ~ 413

송남규, 교광준,

소속 상세정보

송남규 ( ) - 전북대학교 치과대학 구강악안면방사선학교실
교광준 ( ) - 전북대학교 치과대학 구강악안면방사선학교실

KMID : 0378219980280020387

Abstract

GDR, Digora, Ektaspeed plus film scan등의 디지털영상장치로부터 얻은 디지털치근단방
사선영상을 대상으로 선형보간법, 비선형보간법, 면적합모델법, nearest neighbor, cubic
convolution, cubic spline, gray segment expansion법의 7가지 보간법을 시행하여 다음과
같은 결과를 얻었다.
1. 7가지 보간법 중 cubic spline법에서 SNR값이 가장 컸고(75.96dB), 면적합모델법에서
SNR값이 가장 작았다(72..44dB).
2. CDR, Digora 및 film scan영상에서 얻은 SNR값은 차이가 있었다(P<0.05)
3, 7가지 보간법 모두에서 60kVp와 70kVp의 관전압 차이에 따른 SNR값의 차이가 있었
다 (P<0.05). 60kvp에서는 면적합모델법과 나머지 6가지 보간법간의 SNR값의 차이가 있었
으나(P<0.05), 70kvp에서는 7가지 보간법간의 SNR값의 차이는 없었다(P>0.05).
4. 선형보간법과 나머지 6가지 보간법에서 얻은 MTF계수값은 차이가 있었다(P<0.05).
5. 알고리즘 수행시간은 nearest neighbor 법이 가장 빠르게 계산되었으며, 비선형보간법
이 가장 느리게 계산되었다.
6, ROC 평가에서 cubic convolution, cubic spline, gray segment expansion법이 보다 좋
은 상을 보였다.
7. Gray segment expansion법이 7가지 보간법 중 경계부위를 가장 잘 나타내었다
본 연구의 결과는 향후 이를 상용화된 디지털 방사선촬영장치 내에 내장시켜 이용함으로
써 최대의 진단정보를 얻는데 도움을 줄 수 있을 것으로 사료된다.
#초록#
Image resampling is of particular interest in digital radiology. When resampling an
image to a new set of coordinate, there appears blocking artifacts and image changes.
To enhance image quality, interpolation algorithms haute been used. Resampling Is used
to increase the number of points in an image to improve its appearance for display. The
process of interpolation is fitting a continuous function to the discrete points in the
digital periapical image.
The purpose of this study was to determine the effects of the seven interpolation
functions when image resampling in digital periapical images.
The images were obtained by Digora, CDR and scanning of Ektaspeed plus periapical
radiograms on the dry skull and human subject. The subjects were exposed to intraoral
X-ray machine at 60kVp and 70 kVp with exposure time varying between 0.01 and 0.50
second. To determine which interpolation method would provide the better image, seven
functions were compared ; (1) nearest neighbor (2) linear (3) non-linear (4) facet mode)
(5) cubic convolution (6) cubic spline (7) gray segment expansion.
And resampled images were compared in terms of SNR(Signal to Noise Ratio) and
MTF(Modulation Transfer Function) coefficient value.
The obtained results were as follows ;
1. The highest SNR value(75.96dB) was obtained with cubic convolution method and
the lowest SNR value(72.44dB) was obtained with facet model method among seven
interpolation methods.
2. There were significant differences of SNR values among CDR, Digora and film
scan(P<0.05).
3. There were significant differences of SNR values between 60kVp and 70kVp in
seven interpolation methods. There were significant differences of SNR values between
facet model method and those of the other methods at 60kVp(P<0.05), but there were
not significant differences of SNR values among seven interpolation methods at
70kVp(P>0.05)
4. There were significant differences of MTF coefficient values between linear
interpolation method and the other six interpolation methods(P<0.05).
5. The speed of computation time was the fastest with nearest neighbor method and
the slowest with non-linear method.
6. The better image was obtained with cubic convolution, cubic spline and gray
segment method in ROC analysis
7. The better sharpness of edge was obtained with gray segment expansion method
among seven interpolation methods.