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    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/189</link>
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        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60471" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60086" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/60072" />
        <rdf:li rdf:resource="https://scholar.dgist.ac.kr/handle/20.500.11750/59994" />
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    <dc:date>2026-08-03T09:16:01Z</dc:date>
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  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60471">
    <title>Precision enhancement of epidural force-sensing needle with machine learning</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60471</link>
    <description>Title: Precision enhancement of epidural force-sensing needle with machine learning
Author(s): Cho, Gichan; Na, Jongyeol; Lee, Myung Ho; Kwon, Hyun-Jung; Song, Cheol
Abstract: Epidural injection is used in pain intervention, requiring precise needle placement within the epidural space. Traditional techniques, such as loss of resistance and fluoroscopy-guided procedures, have limitations, including reliance on subjective assessment and radiation exposure. We proposed an optical force-sensing probe with an offset criterion of the needle tip-distal end to enhance the precision of puncture detection. The offset between the needle tip and the force-sensing probe is adjusted using a piezoelectric motor-based system with feedback position control. A Long Short-Term Memory model is also trained to detect the puncture. Insertion test on silicone phantom and ex-vivo specimens demonstrates that the system's offset range for enhancing precision of puncture detection is between 0.6 mm and 1 mm. Compared to the offset in the previous study, the AUC score of puncture detection increased from 0.61 to 0.86. This approach secures the improvement of puncture detection reliability in robot-assisted epidural injection.</description>
    <dc:date>2026-11-30T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60086">
    <title>손 떨림 보정 및 광학 거리 제어를 이용한 비접촉 휴대형 공초점 망막 내시현미경 시스템</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60086</link>
    <description>Title: 손 떨림 보정 및 광학 거리 제어를 이용한 비접촉 휴대형 공초점 망막 내시현미경 시스템
Author(s): 이명호; 조기찬; 임진택; 나종열; 송철
Abstract: We  present  a  novel  handheld  confocal  endomicroscopy  system  designed  for  non-contact,  high-resolution  retinal  imaging,  integrating  motorized  stabilization  and  tremor  prediction.  The  system  combines  a custom PZT-driven Lissajous scanning probe, and a common-path swept-source optical coherence tomography (CPSS-OCT)  sensor  for  depth  tracking  for  real-time  tremor  compensation.  This  multimodal  platform  allows continuous imaging at the cellular level without requiring probe-to-tissue contact, addressing critical limitations of conventional probe-based confocal laser endomicroscopy(pCLE) systems. Experimental evaluations using ex-vivo bovine retina samples demonstrated significant enhancements in image clarity, with the CR score increasing by 48.43% under active tremor control. The proposed architecture offers improved image stability, precise axial focusing, and handheld portability, making it a strong candidate for clinical applications in retinal diagnostics and intraoperative imaging.</description>
    <dc:date>2025-06-26T15:00:00Z</dc:date>
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  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/60072">
    <title>비전 기반 3차원 자세 추정을 이용한  인간 로봇 충돌 방지 시스템</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/60072</link>
    <description>Title: 비전 기반 3차원 자세 추정을 이용한  인간 로봇 충돌 방지 시스템
Author(s): 나종열; 송철
Abstract: As  human-robot  collaboration  becomes  increasingly prevalent  in  medical  and  industrial  settings,  the  risk of  collisions  is  rising  due  to  shared  workspaces. Traditional  approaches  rely  on  stopping  mechanisms or  external  sensors,  which  may  limit  system  adaptability.      This  study  proposes  a  camera-based  method  utilizing  a  convolutional  neural  network  (CNN)  to  estimate  the  3D  joint  coordinates  of  robots and  humans  within  a  unified  camera  coordinate frame.  It  estimates  the  3D  positions  of  the  robot&amp;apos;s seven  joints  with  an  average  error  below  5.5  mm,  enabling  real-time  collision  risk  assessment  through joint  distance  computation.  This  vision-based approach  provides  precise  spatial  awareness  without requiring  additional  external  sensors,  enhancing safety  and  operational  efficiency.</description>
    <dc:date>2025-06-25T15:00:00Z</dc:date>
  </item>
  <item rdf:about="https://scholar.dgist.ac.kr/handle/20.500.11750/59994">
    <title>Handheld Confocal Endomicroscope System with Tremor Compensation for Retinal Imaging</title>
    <link>https://scholar.dgist.ac.kr/handle/20.500.11750/59994</link>
    <description>Title: Handheld Confocal Endomicroscope System with Tremor Compensation for Retinal Imaging
Author(s): Lee, Myung Ho; Cho, Gichan; Im, Jintaek; Na, Jongyeol; Song, Cheol
Abstract: Advancements in biophotonics have driven the development of miniaturized imaging probes for high-resolution in vivo imaging. Probe-based confocal laser endomicroscopy (pCLE) enables cellular-level visualization of tissues but remains challenging for retinal imaging due to the need for non-contact operation, tremor compensation, and precise focal control. This study introduces a novel handheld confocal endomi-croscope system that integrates a custom-built imaging probe, an optical coherence tomography (OCT) distance sensor, and motor-assisted tremor suppression to improve imaging stability and resolution. The system employs a fiber-based common-path swept-source OCT (CPSS-OCT) sensor to maintain a stable focal distance while compensating for involuntary hand tremors using motorized stabilization. A gated recurrent unit (GRU)-based tremor prediction algorithm further enhances image stability. The imaging probe features a PZT tube-driven fiber cantilever resonance for Lissajous scanning, providing a wide field of view with minimal image distortion. In experiments using bovine eye samples, the CR score improved from 0.318 to 0.472, with a 48.43% increase in the in-focus condition when tremor compensation was activated, confirming enhanced image clarity and stability. Experimental results demonstrate that the system effectively stabilizes imaging, reduces motion artifacts, and ensures high-resolution, non-contact retinal imaging. By addressing the limitations of conventional pCLE devices, this system represents a significant advancement in ophthalmic imaging and can potentially improve retinal diagnostics and precision-guided interventions.</description>
    <dc:date>2025-10-21T15:00:00Z</dc:date>
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