3 research outputs found

    μ˜λŒ€μƒμ„ λŒ€μƒμœΌλ‘œ ν•œ 디지털 기반 ν•΄λΆ€ν•™ κ΅μœ‘κ³Όμ • 개발과 κ΅μœ‘νš¨κ³Όμ— κ΄€ν•œ 연ꡬ

    Get PDF
    ν•™μœ„λ…Όλ¬Έ(박사) -- μ„œμšΈλŒ€ν•™κ΅λŒ€ν•™μ› : μ˜κ³ΌλŒ€ν•™ μ˜ν•™κ³Ό, 2023. 2. μ‹ λ™ν›ˆ.전톡적인 카데바 ν•΄λΆ€λŠ” λ‹€μ–‘ν•œ 이유둜 인해 κΈ‰κ²©ν•˜κ²Œ κ°μ†Œν•˜μ˜€κ³ , 졜근 λͺ‡ λ…„ λ™μ•ˆ 기술 λ°œμ „μœΌλ‘œ 의료 ꡐ윑 λΆ„μ•Όμ—μ„œλŠ” λ‹€μ–‘ν•œ 디지털 기기와 μ†Œν”„νŠΈμ›¨μ–΄κ°€ μƒμ‚°λ˜κ³  μžˆλ‹€. λ³Έ 논문은 디지털 κΈ°μˆ μ„ μ μš©ν•œ κ΅μœ‘κ³Όμ •μ„ κ°œλ°œν•˜κ³  디지털 기반 ν•΄λΆ€ν•™ ꡐ윑의 ν•™μŠ΅νš¨κ³Όμ™€ λ§Œμ‘±λ„λ₯Ό μ•Œμ•„λ³΄κΈ° μœ„ν•΄ 두 가지 μ—°κ΅¬λ‘œ μ§„ν–‰λ˜μ—ˆλ‹€. 첫번째 μ—°κ΅¬μ—μ„œλŠ” 2019λ…„ μ½”λ‘œλ‚˜ λ°”μ΄λŸ¬μŠ€ λ°œμƒμœΌλ‘œ 의료 ꡐ윑과 의료 μ‹œμŠ€ν…œμ΄ μ•½ν™”λ˜μ—ˆλ‹€. λ”°λΌμ„œ λ³Έ μ—°κ΅¬λŠ” 온라인 μˆ˜μ—…μ˜ λ„μž…κ³Ό 3차원 ν•΄λΆ€ν•™ μ–΄ν”Œλ¦¬μΌ€μ΄μ…˜μ„ ν†΅ν•œ μˆ˜μ •λœ 일정이 ν•™μƒλ“€μ˜ 학업성취도와 λ§Œμ‘±λ„μ— λ―ΈμΉ˜λŠ” 영ν–₯을 λΆ„μ„ν•˜μ˜€λ‹€. ν•΄λΆ€ν•™ κ΅μœ‘μ€ μ½”λ‘œλ‚˜19 λ²”μœ ν–‰μœΌλ‘œ 인해 3개의 ν•˜μœ„λ‹¨μœ„(μƒν•˜, λͺΈν†΅, 머리와 λͺ©)둜 λ‚˜λ‰˜μ—ˆλ‹€. 온라인 κ°•μ˜λ₯Ό μ œμ™Έν•œ 카데바 해뢀와 ν•„κΈ° 및 μ‹€κΈ°μ‹œν—˜μ€ 각각 50μ—¬λͺ…μ”© 3개의 반으둜 λ‚˜λ‰˜μ–΄ 진행됐닀. λ˜ν•œ, ν•™μƒλ“€μ˜ 학업성취도λ₯Ό 3개의 ν•˜μœ„ λ‹¨μœ„μ—μ„œ ν•„κΈ°μ‹œν—˜κ³Ό μ‹€κΈ°μ‹œν—˜μ„ ν†΅ν•˜μ—¬ ν‰κ°€ν•˜μ˜€κ³ , μˆ˜μ •λœ ν•΄λΆ€ν•™ 일정에 λŒ€ν•œ 섀문지λ₯Ό μž‘μ„±ν•˜μ˜€λ‹€. ν•„κΈ°μ‹œν—˜κ³Ό μ‹€κΈ°μ‹œν—˜ μ μˆ˜λŠ” λŒ€λΆ€λΆ„ 2019년에 λΉ„ν•΄ 2020년에 크게 λ–¨μ–΄μ‘Œλ‹€. λ‹€λ§Œ, 가상해뢀학 μ–΄ν”Œλ¦¬μΌ€μ΄μ…˜μ„ ν™œμš©ν•œ λͺΈν†΅ μ„Έμ…˜μ—μ„œλŠ” 2020λ…„ μ‹€κΈ°μ‹œν—˜ μ μˆ˜κ°€ 2019년보닀 μ›”λ“±νžˆ λ†’μ•˜λ‹€. 70% 이상(νŒ”λ‹€λ¦¬μ™€ λͺΈν†΅ μ„Έμ…˜)κ³Ό 53% (머리와 λͺ© μ„Έμ…˜) 학생듀이 λŒ€λ©΄ μ‹€μŠ΅μ—μ„œ 해뢀학을 κ³΅λΆ€ν•˜λŠ” 데 큰 어렀움이 μ—†λ‹€κ³  λ³΄κ³ ν–ˆλ‹€. λ˜ν•œ, 50% μ΄μƒμ˜ 학생듀이 λͺ¨λ“  μ„Έμ…˜μ—μ„œ μ–΄ν”Œλ¦¬μΌ€μ΄μ…˜μ˜ μƒλ‹Ήν•œ 도움을 λ°›μ•˜λ‹€. λ‘λ²ˆμ§Έ μ—°κ΅¬μ—μ„œ μ˜€λŠ˜λ‚ μ˜ λͺ¨λ“  μ˜ν•™ λΆ„μ•ΌλŠ” 디지털 μ „ν™˜μ˜ 영ν–₯을 크게 λ°›λŠ”λ‹€. λ³Έ μ—°κ΅¬λŠ” μ˜ν•™κ΅μœ‘μ—μ„œ 디지털 μ—­λŸ‰μ˜ 톡합 ν•„μš”μ„±μ„ μ„€λͺ…ν•˜κ³ , ν•™λΆ€ κ΅μœ‘μ—μ„œ μ΄λŸ¬ν•œ μ—­λŸ‰μ˜ κ΅¬ν˜„μ΄ μ–΄λ–»κ²Œ μ΄λ£¨μ–΄μ§ˆ 수 μžˆλŠ”μ§€ 디지털 기반 ν•΄λΆ€ν•™ ꡐ윑 μ»€λ¦¬ν˜λŸΌμ„ μ œμ‹œν•œλ‹€. 이 μ—°κ΅¬λŠ” ꡐ차 λ¬΄μž‘μœ„ λŒ€μ‘° μ‹œν—˜μ΄μ—ˆλ‹€. 인체해뢀학과 μ‹ κ²½ν•΄λΆ€ν•™ μ‹€μŠ΅μ€ 3λΆ„λ°˜ (A반, B반, C반)으둜, 1ν•™λ…„ μ˜λŒ€μƒμ€ 가상 ν•΄λΆ€ 집단 (가상 ν•΄λΆ€ --> 카데바 ν•΄λΆ€)κ³Ό 카데바 ν•΄λΆ€ 집단 (카데바 ν•΄λΆ€ --> 가상 ν•΄λΆ€)으둜 λ¬΄μž‘μœ„ λΆ„λ₯˜λ˜μ—ˆλ‹€. 가상 ν•΄λΆ€μ‹€μŠ΅μ€ ν—€λ“œλ§ˆμš΄ν‹°λ“œ λ””μŠ€ν”Œλ ˆμ΄, νƒœλΈ”λ¦Ώ, μ‹€λ¬Ό 크기의 ν„°μΉ˜ μŠ€ν¬λ¦°μ„ μ‚¬μš©ν–ˆλ‹€. ν€΄μ¦ˆ 1은 첫번째 가상 ν•΄λΆ€μ‹€μŠ΅ λ˜λŠ” 카데바 ν•΄λΆ€μ‹€μŠ΅ 후에 ν•΄λΆ€ν•™ 지식을 λΉ„κ΅ν•˜κΈ° μœ„ν•΄ μ§„ν–‰λ˜μ—ˆλ‹€. ν€΄μ¦ˆ 2와 μ„€λ¬Έμ‘°μ‚¬λŠ” λͺ¨λ“  κ°€μƒν•΄λΆ€μ‹€μŠ΅κ³Ό 카데바 ν•΄λΆ€μ‹€μŠ΅μ΄ 끝날 λ•Œ μˆ˜ν–‰λ˜μ—ˆλ‹€. 인체해뢀학 μ‹€μŠ΅μ˜ 경우, ν€΄μ¦ˆ1의 평균 μ΄μ μ—μ„œλŠ” μœ μ˜λ―Έν•œ 차이가 μ—†μ—ˆλ‹€. κ·ΈλŸ¬λ‚˜, Cλ°˜μ—μ„œλŠ” 가상 ν•΄λΆ€ ꡐ윑이 카데바 κ΅μœ‘λ³΄λ‹€ μ›”λ“±νžˆ 높은 학업성취도λ₯Ό λ³΄μ˜€λ‹€. 디지털 κΈ°κΈ°λ“€ μ€‘μ—μ„œ, λŒ€λΆ€λΆ„μ˜ 학생듀은 νƒœλΈ”λ¦Ώ 기반 ν•™μŠ΅μ΄ 효과적인 ν•™μŠ΅ 방법이라고 μƒκ°ν–ˆλ‹€. μ‹ κ²½ν•΄λΆ€ν•™ μ‹€μŠ΅μ—μ„œλŠ” 가상 ν•΄λΆ€ ꡐ윑이 카데바 κ΅μœ‘λ³΄λ‹€ ν†΅κ³„μ μœΌλ‘œ μœ μ˜ν•˜κ²Œ 높은 ν•™μ—… 성취도λ₯Ό λ³΄μ—¬μ£Όμ—ˆλ‹€. λŒ€λΆ€λΆ„μ˜ 학생듀은 3차원 디지털 기반 ν•™μŠ΅μ΄ μ‹œμ²΄ 해뢀학에 λŒ€ν•œ 이해λ₯Ό ν–₯μƒμ‹œμΌ°λ‹€κ³  λ³΄κ³ ν•˜κ³ , 디지털 μ‹€μŠ΅ κΈ°κΈ°λ₯Ό ν†΅ν•œ 가상 ν•΄λΆ€ν•™ μ‹€μŠ΅ κ²½ν—˜μ— κ°€μž₯ λ§Œμ‘±ν–ˆλ‹€. λ³Έ μ—°κ΅¬λŠ” μ˜ν•™κ΅μœ‘μ—μ„œ 디지털 기반 ν•΄λΆ€ν•™ ꡐ윑의 κ°€λŠ₯성을 보여주고 디지털 기반 ν•΄λΆ€ν•™ κ΅μœ‘μ€ 전톡적인 카데바 κ΅μœ‘μ„ κ°•ν™”ν•˜λŠ” ν˜μ‹ μ μΈ ν•™μŠ΅ κ²½ν—˜μ„ μ œκ³΅ν•  수 μžˆμ„ 것이닀.Traditional cadaver dissection has been drastically reduced for various reasons, and technological advances in recent years have produced a variety of digital devices and software in medical education. This thesis was conducted in two studies to develop curriculums applying digital technologies and compare digital-based anatomy education with traditional anatomy education to find out the learning efficacy and satisfaction. In the first study, the coronavirus disease 2019 (COVID-19) outbreak weakened medical education and healthcare systems. Therefore, the effect of the modified schedule with the introduction of online classes and a three-dimensional anatomy application on students' academic achievement and satisfaction was analyzed. Anatomy education was divided into three regional units (the upper and lower limbs, trunk, and head and neck) due to COVID-19. The schedule was mixed with simultaneous and rotating schedules. Except for online lectures, cadaver dissections, and written and practical examinations were conducted in three classes of approximately 50 students each. Furthermore, students' performance was assessed using three sets of written and practical examinations, and they completed a questionnaire regarding modified anatomy laboratory schedules. Most of the written and practical examination scores significantly decreased in 2020 compared to 2019. However, in the trunk session that used the virtual anatomy application, the score on the practical examination in 2020 was significantly higher than in 2019. Over 70% (upper and lower limbs and trunk sessions) and 53% (head and neck session) students reported no significant difficulty in the face-to-face anatomy laboratory. In addition, over 50% of students received considerable help with the anatomy application in all sessions. In the second study, the digital revolution has impacted all medical disciplines. Therefore, the need for digital competencies in medical education and how to incorporate them into undergraduate training using a digital-based anatomy curriculum was addressed. This was a crossover randomized controlled trial. In both Human Anatomy and Neuroanatomy laboratories, there were three classes (class A, B, and C) in the first year of the Department of Medicine, and students were randomized into two groups: the virtual group (virtual dissection --> cadaver dissection) and the cadaver group (cadaver dissection --> virtual dissection). The virtual dissection laboratory was conducted via head-mounted displays, tablets, and a life-sized touchscreen. Quiz 1 (Q1) was tested following the first virtual or cadaver dissections. Quiz 2 (Q2) and a survey were conducted at the end of the final procedure in each training modality. Regarding the Human Anatomy laboratory, there was no significant difference in the Q1 mean total score. However, in class C, virtual education showed significantly higher academic achievement than cadaver education. Most students felt tablet-based learning was an effective study method among the digital lab resources. Regarding the Neuroanatomy laboratory, virtual education showed significantly higher academic achievement in Q1 than cadaver education. Most students reported that digital-based learning enhanced their understanding of cadaveric anatomy. Students were most satisfied with their experiences of virtual anatomy education through digital lab resources. These studies demonstrate the potential for digital-based anatomy education in medical education. Digital-based anatomy education can provide innovative learning experiences augmenting traditional cadaver education.Chapter 1 The Metaverse: A New Challenge for the Anatomy Education 01 Challenges Facing Anatomy Education 02 Applications of Metaverse in Medical Education 05 The List of Devices for Anatomy Education 08 Mobile Devices 08 Virtual Dissection Tables 09 Head-Mounted Displays 10 Digital Anatomy Applications 13 Contents' Scenarios for Digital Anatomy Education 15 Chapter 2 Exploring Medical Students' Performance and Satisfaction of the Modified Anatomy Schedules and a Digital Software During COVID-19 Pandemic 17 Introduction 18 Study Goals and Questions 20 Materials and Methods 21 Results 28 Discussion 32 Chapter 3 Virtual Anatomy Laboratory Education: A Randomized Controlled Trial Compared to Cadaver Dissection 36 Introduction 37 Study Goals and Questions 39 Materials and Methods 40 Results 48 Discussion 64 Conclusion 69 References 71 Supporting Information 85 Abstract in Korean 94 Acknowledgement 96λ°•

    쑰직 투λͺ…ν™”λ₯Ό μ΄μš©ν•œ μ₯μ™€ μ‚¬λžŒμ˜ 전체 μž₯신경계 3차원 μ‹œκ°ν™” 및 μ •λŸ‰ν™”

    No full text
    ν•™μœ„λ…Όλ¬Έ (석사) -- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : μ˜κ³ΌλŒ€ν•™ μ˜ν•™κ³Ό, 2021. 2. ν™©μ˜μΌ.BACKGROUND & AIMS: Nowadays, state-of-the-art tissue clearing methods enable visualization of the thicker tissue section or even whole organ imaging, by increasing tissue transparency and enhancing the antigen-antibody reaction. The goal of this research was to establish a 3D imaging method for the whole gastrointestinal (GI) tract that yields more information and insight about the enteric nervous system (ENS) than traditional 2D tissue section imaging. This approach will improve a comprehensive understanding of research purpose and diagnosis of human diseases, such as Hirschsprung disease, bowel motility disorders, or inflammatory bowel disease (IBD). The present study optimized a technique to image transgenic fluorescence mice and human ENS that express fluorescent neuron-specific class β…’ beta-tubulin (Tuj1), neuronal nitric oxide synthase (nNOS), choline acetyltransferase (ChAT), and RNA binding proteins (HuC/D) in 3 dimensions. METHODS: Visualization and quantification of the digestive organs (e.g. esophagus, stomach, small intestine, and colon) in mice and humans were carried out through various techniques. A method, encompassing tissue clearing, immunohistochemistry (IHC), confocal microscopy, light sheet fluorescence microscopy (LSFM), and quantitative analysis of full-thickness bowel without tissue sections, had been established for 3D imaging at high resolution. Furthermore, using surface rendering, volume rendering for all channels, fluorescence thresholding, and background subtraction, tools from in IMARIS, cleared tissues could be visualized in an accurate 3D structure. RESULTS: The multiscale structural decomposition of mouse and human ENS was clearly visualized in 3D. The tissue clearing method could image the complex ENS network structure of myenteric plexus, submucosal plexus, and mucosal nerves. Similarly, the 3D ENS network structure of the esophagus (16 Γ— 14 Γ— 5.3 mm) and colon (1.2 Γ— 1.3 Γ— 1.4 mm) samples were visualized in mouse and human, respectively. I investigated the cholinergic ENS structure through the whole GI tract and quantified the number of cell bodies and cell bodies per ganglion in myenteric and submucosal plexus in mouse (n=3). To identify the hubness of the myenteric plexus in mouse, I measured the number of ganglia and bridges without cell bodies that connected the ganglion. Quantitative data for myenteric plexus and submucosal plexus showed relatively different aspects. CONCLUSIONS: This study was the first to visualize the mouse and human whole ENS in three dimensions with no sectioning and microanatomy. The cytoarchitecture of the mouse tissues could be quantitatively analyzed, preserving the tissue structure, and providing more accurate data with tissue clearing. A quantitative analysis method of structure phenotypes in mouse will illuminate the potential usefulness of this technology. For GI motility disorders, this novel technology will unravel the extensive spatial 3D network structure of neuro-immune interaction.λ°°κ²½ 및 λͺ©μ : μ˜€λŠ˜λ‚ μ˜ μ΅œμ²¨λ‹¨ 생체쑰직 투λͺ…ν™” κΈ°μˆ μ€ 쑰직 투λͺ…화와 항원-ν•­μ²΄μ˜ λ°˜μ‘μ„ μ΄‰μ§„μ‹œν‚΄μœΌλ‘œμ¨ λ‘κΊΌμš΄ 쑰직 λ˜λŠ” μ „ 기관을 μ‹œκ°ν™” ν•  수 있게 ν•œλ‹€. λ³Έ μ—°κ΅¬λŠ” μœ„μž₯관에 λŒ€ν•œ 쑰직의 2차원 이미지보닀 μž₯신경계에 λŒ€ν•œ 정보와 톡찰λ ₯을 더 많이 μ‚°μΆœν•˜λŠ” 3차원 μ˜μƒ 방법을 κ°œλ°œν•˜λŠ” 것이닀. μ΄λŸ¬ν•œ 접근방식은 염증성 μž₯μ§ˆν™˜μ΄λ‚˜ μž₯ μš΄λ™μ„± μž₯애와 같은 인간 μ§ˆλ³‘μ— λŒ€ν•œ 연ꡬ λͺ©μ κ³Ό 진단에 λŒ€ν•œ 포괄적인 이해λ₯Ό ν–₯μƒμ‹œν‚¬ 수 있으며 λ”°λΌμ„œ ν˜•μ§ˆμ „ν™˜ μ₯μ™€ μΈκ°„μ˜ μž₯μ‹ κ²½κ³„μ—μ„œ 베타 β…’ νŠœλΈ”λ¦° (Tuj1), μ‹ κ²½μ„± μ‚°ν™”μ§ˆμ†Œ ν•©μ„±νš¨μ†Œ (nNOS)와 μ½œλ¦°μ•„μ„Έν‹ΈνŠΈλžœμŠ€νΌλΌμ•„μ œ (ChAT), ν˜•κ΄‘μ‹ κ²½μ˜ RNA κ²°ν•© λ‹¨λ°±μ§ˆ (HuC/D)을 3μ°¨μ›μœΌλ‘œ μ‹œκ°ν™” ν•˜λŠ” 기법을 μ΅œμ ν™”ν•˜μ˜€λ‹€. 방법: μ₯μ™€ μ‚¬λžŒμ˜ μ†Œν™”κΈ°κ΄€ (식도, μœ„, μ†Œμž₯, λŒ€μž₯)을 μ‹œκ°ν™”ν•˜κ³  μ •λŸ‰ν™” ν•˜κΈ° μœ„ν•΄ λ‹€μ–‘ν•œ κΈ°λ²•μœΌλ‘œ 연ꡬλ₯Ό μˆ˜ν–‰ν•˜μ˜€λ‹€. κ³ ν•΄μƒλ„μ˜ 3차원 μ˜μƒμ„ μ–»κΈ° μœ„ν•΄ μ₯μ™€ μ‚¬λžŒμ˜ 쑰직을 μ‚¬μš©ν•˜μ—¬ 쑰직 투λͺ…ν™” 기법, 면역화학염색 (IHC), 곡초점 ν˜„λ―Έκ²½, μ‹œνŠΈ ν˜•κ΄‘ ν˜„λ―Έκ²½ (LSFM)κ³Ό 전체 μœ„μž₯κ΄€ λ‘κ»˜μ— λŒ€ν•œ μ •λŸ‰μ  뢄석을 μˆ˜λ°˜ν•œ 방법듀이 κ°œλ°œλ˜μ—ˆλ‹€. λ‚˜μ•„κ°€ IMARIS의 툴인 ν‘œλ©΄ λ Œλ”λ§, λͺ¨λ“  채널에 λŒ€ν•œ λ³Όλ₯¨ λ Œλ”λ§, ν˜•κ΄‘ μž„κ³„μΉ˜, λ°°κ²½ 제거 등을 μ‚¬μš©ν•˜μ—¬ λ³Όλ₯¨μ„ μΈ‘μ •ν•  수 μžˆλŠ” μ •ν™•ν•œ 3D ꡬ쑰λ₯Ό 얻을 수 μžˆμ—ˆλ‹€. κ²°κ³Ό: μ₯μ™€ μ‚¬λžŒμ˜ μž₯μ‹ κ²½κ³„λŠ” λ‹€μ–‘ν•œ 규λͺ¨μ˜ 3μ°¨μ›μœΌλ‘œ μ‹œκ°ν™” λ˜μ—ˆλ‹€. 큰 μ‘°μ§μ—μ„œ 3μ°¨μ›μœΌλ‘œ 면역염색과 이미징이 κ°€λŠ₯ν•œ 쑰직 투λͺ…ν™” 방법은 κ·Όμœ‘μΈ΅μ‹ κ²½μ–ΌκΈ°, μ λ§‰ν•˜μ‹ κ²½μ΄κ³Ό 점막 μ‹ κ²½λ“€μ˜ λ„€νŠΈμ›Œν¬λ₯Ό λ³΄μ—¬μ£Όμ—ˆλ‹€. λ§ˆμ°¬κ°€μ§€λ‘œ, μ₯μ˜ 식도 (16 Γ— 14 Γ— 5.3 mm) 와 μ‚¬λžŒμ˜ λŒ€μž₯ (1.2 Γ— 1.3 Γ— 1.4 mm) 쑰직 μƒ˜ν”Œμ—μ„œλ„ 3차원 μž₯μ‹ κ²½ λ„€νŠΈμ›Œν¬ ꡬ쑰λ₯Ό 잘 λ³΄μ—¬μ£Όμ—ˆλ‹€. μ₯(n=3)λ₯Ό μ‚¬μš©ν•˜μ—¬ μž₯ 전체에 λΆ„ν¬ν•˜λŠ” ChAT의 μ‹ κ²½ ꡬ쑰λ₯Ό μ—°κ΅¬ν•˜κ³ , λ‘κ°œμ˜ μ£Όμš” μΈ΅μ—μ„œ 세포체와 μ‹ κ²½μ ˆ λ‹Ή 세포체λ₯Ό μ •λŸ‰ν™” ν•˜μ˜€λ‹€. κ·Όμœ‘μ‹ κ²½μ–ΌκΈ°μ˜ 연결도λ₯Ό ν™•μΈν•˜κΈ° μœ„ν•΄ μ‹ κ²½μ ˆμ˜ μˆ˜μ™€ μ‹ κ²½μ ˆκ³Ό μ‹ κ²½μ ˆμ„ μ΄λŠ” 닀리도 μΈ‘μ •ν•˜μ˜€λ‹€. κ·Όμœ‘μΈ΅μ‹ κ²½μ–ΌκΈ°μ™€ μ λ§‰ν•˜μ‹ κ²½μ΄μ˜ μ •λž΅μ  λ°μ΄ν„°λŠ” 비ꡐ적 μ„œλ‘œ λ‹€λ₯Έ 양상을 λ³΄μ—¬μ£Όμ—ˆλ‹€. 더 λ‚˜μ•„κ°€ μ₯μ—μ„œ μ–΅μ œμ„± μ‹ κ²½κ³Ό ν₯λΆ„μ„± 신경을 λ©΄μ—­ μ—Όμƒ‰ν•˜λŠ”λ° μ„±κ³΅ν•˜μ˜€λ‹€. κ²°λ‘ : 이 μ—°κ΅¬λŠ” μ₯μ™€ μ‚¬λžŒμ˜ 쑰직 투λͺ…ν™” κΈ°μˆ μ— μ ν•©ν•˜κ³  μž₯μ‹ κ²½κ³„μ˜ ꡬ쑰와 μ‹ κ²½νšŒλ‘œ 연ꡬ에 적용 κ°€λŠ₯성을 높일 것이닀. 특히, 콜린 μž‘λ™μ„± λ‰΄λŸ°μ˜ 수λ₯Ό μ •λŸ‰ν™”ν•˜λŠ” 방법에 λŒ€ν•œ 검증을 μ œκ³΅ν•œλ‹€. μ₯μ˜ ꡬ쑰 ν‘œν˜„ν˜•μ˜ μ •λŸ‰μ  뢄석 방법은 진단 λ§ˆμ»€λ‘œμ„œ 이 기술의 잠재적인 μœ μš©μ„±μ„ μ‘°λͺ…ν•˜κ³  μž₯ μš΄λ™μ„± μž₯μ• μ˜ 경우 이 μƒˆλ‘œμš΄ 기술이 μ‹ κ²½λ©΄μ—­μ˜ μƒν˜Έμž‘μš©μ— λŒ€ν•œ κ΄‘λ²”μœ„ν•œ 3차원 λ„€νŠΈμ›Œν¬ ꡬ쑰λ₯Ό 밝힐 것이닀.β…°. Abstract β…³. Contents β…΄. List of tables β…΅. List of figures β…Έ. List of abbreviations 1. Introduction 6. Materials and Methods 11. Results 21. Discussion 26. References 70. Abstract (Korean)Maste
    corecore