본문 바로가기
KERD
논문KCI 등재

초음파 영상 특성을 이용한 실시간 초음파 영역 추출방법

Real-time Ultrasound Contexts Segmentation Based on Ultrasound Image Characteristic

0

조회

0

다운로드

0

인용

0

참고문헌

키워드

초록

In ultrasound telemedicine, it is important to reduce the size of the data by compressing the ultrasound image when sending it. Ultrasound images can be divided into image context and other information consisting of patient ID, date, and several letters. Between them, ultrasound context is very important information for diagnosis and should be securely preserved as much as possible. In several previous papers, ultrasound compression methods were proposed to compress ultrasound context and other information into different compression parameters. This ultrasound compression method minimized the loss of ultrasound context while greatly compressing other information. This paper proposed the method of automatic segmentation of ultrasound context to overcome the limitation of the previously described ultrasound compression method. This algorithm was designed to robust for various ultrasound device and to enable real-time operation to maintain the benefits of ultrasound imaging machine. The operation time of extracting ultrasound context through the proposed segmentation method was measured, and it took 311.11 ms. In order to optimize the algorithm, the ultrasound context was segmented with down sampled input image. When the resolution of the input image was reduced by half, the computational time was 126.84 ms. When the resolution was reduced by one-third, it took 45.83 ms to segment the ultrasound context. As a result, we verified through experiments that the proposed method works in real time.

Abstract

In ultrasound telemedicine, it is important to reduce the size of the data by compressing the ultrasound image when sending it. Ultrasound images can be divided into image context and other information consisting of patient ID, date, and several letters. Between them, ultrasound context is very important information for diagnosis and should be securely preserved as much as possible. In several previous papers, ultrasound compression methods were proposed to compress ultrasound context and other information into different compression parameters. This ultrasound compression method minimized the loss of ultrasound context while greatly compressing other information. This paper proposed the method of automatic segmentation of ultrasound context to overcome the limitation of the previously described ultrasound compression method. This algorithm was designed to robust for various ultrasound device and to enable real-time operation to maintain the benefits of ultrasound imaging machine. The operation time of extracting ultrasound context through the proposed segmentation method was measured, and it took 311.11 ms. In order to optimize the algorithm, the ultrasound context was segmented with down sampled input image. When the resolution of the input image was reduced by half, the computational time was 126.84 ms. When the resolution was reduced by one-third, it took 45.83 ms to segment the ultrasound context. As a result, we verified through experiments that the proposed method works in real time.

참고문헌 (15)

  1. Larobina M, "Medical Image File Formats", J Digit Imaging, 27(2), pp.200~206 (2014)
  2. Ferreira AC, "Teleultrasound : Historical Perspective and Clinical Application", Int J Telemed, 2015, pp.1~11 (2015)
  3. Sengupta PP, "Feasibility of Intercity and Trans-Atlantic Telerobotic Remote Ultrasound : Assessment Facilitated by a Nondedicated Bandwidth Connection", JACC : Cardivascular Imaging, 7(8), pp.804~809 (2014)
  4. Vieyres P, "The TERESA project : from space research to ground teleechography", Ind Rob, 30(1), pp.77~82 (2003)
  5. Arbeille P, "Use of a Robotic Arm to Perform Remote Abdominal Telesonography", AJR Am J Roentgenol, 188(4), pp.317~322 (2007)
  6. Arbeille P, "Tele-Operated Echocardiography Using a Robotic Arm and an Internet Connection", Ultrasound Med Biol, 40(10), pp.2521~2529 (2014)
  7. Schlosser J, "Telerobotics System Concept for Real-Time Soft-Tissue imaging during Radiotherapy Beam Delivery", Med Phys, 37(12), pp.6357~6367 (2010)
  8. Boman K, "Remotecontrolled robotic arm for real-time echocardiography: the diagnostic future for patients in rural areas", Telemed J E Health, 15(2), pp.142~147 (2009)
  9. Binkhuysen FHB, "Teleradiology : evolution and concepts", European Journal of Radiology, 78(2), pp.205~209 (2011)
  10. Edler I, "Use of ultrasonic reflectoscope for continuous recording of movements of heart walls 1954", Clin Physiol Funct Imaging, 24(3), pp.118~136 (2004)
  11. Ansari MA, "Context based medical image compression for ultrasound images with contextual set partitioning in hierarchical trees algorithm", Adv Eng Software, 40(7), pp.487~496 (2009)
  12. Hosseinin SM, "Medical ultrasound image compression using contextual vector quantization", Comput Biol Med, 42(7), pp.743~750 (2012)
  13. Kaur L, "Medical ultrasound image compression using joint optimization of thresholding quantization and best-basis selection of wavelet packets", Digital Signal Processing, 17(1), pp.189~198 (2007)
  14. Liu Z, "The effects of interactie latency on exploratory visual analysis", IEEE Trans Vis Comput Graph, 20(12), pp.2122~2131 (2014)
  15. Card SK, "The psychology of human computer interaction", pp.23~44 (1983)

관련 논문AI추천

이 간행물의 다른 논문 (9건)