• 제목/요약/키워드: 의공학융합

검색결과 63건 처리시간 0.025초

의료영상 분야를 위한 설명가능한 인공지능 기술 리뷰 (A review of Explainable AI Techniques in Medical Imaging)

  • 이동언;박춘수;강정운;김민우
    • 대한의용생체공학회:의공학회지
    • /
    • 제43권4호
    • /
    • pp.259-270
    • /
    • 2022
  • Artificial intelligence (AI) has been studied in various fields of medical imaging. Currently, top-notch deep learning (DL) techniques have led to high diagnostic accuracy and fast computation. However, they are rarely used in real clinical practices because of a lack of reliability concerning their results. Most DL models can achieve high performance by extracting features from large volumes of data. However, increasing model complexity and nonlinearity turn such models into black boxes that are seldom accessible, interpretable, and transparent. As a result, scientific interest in the field of explainable artificial intelligence (XAI) is gradually emerging. This study aims to review diverse XAI approaches currently exploited in medical imaging. We identify the concepts of the methods, introduce studies applying them to imaging modalities such as computational tomography (CT), magnetic resonance imaging (MRI), and endoscopy, and lastly discuss limitations and challenges faced by XAI for future studies.

자착식 부틸고무 방수시트의 재생고무 증량 배합에 따른 물성변화 특성 (Characteristics of Change in Properties of Self-Adhesive Butyl Rubber Waterproofing Sheet by Increasing the Amount of Reclaimed Rubber)

  • 최수영;박진상;최성민;권영화;김영근;오상근
    • 한국건축시공학회:학술대회논문집
    • /
    • 한국건축시공학회 2021년도 가을 학술논문 발표대회
    • /
    • pp.252-253
    • /
    • 2021
  • In this study, butyl rubber, which is the main material constituting the self-adhesive butyl rubber waterproofing sheet, was mixed with reclaimed rubber, and tensile strength, tear strength, peeling resistance strength, and adhesion strength were measured for sample prepared by mixing ratio. As a result, it was confirmed that peeling resistance strength and adhesion strength decreased as the reclaimed rubber content increased, and tensile strength and tear strength did not change significantly.

  • PDF

MediaPipe Framework를 이용한 얼굴과 손의 경혈 판별을 위한 Computer Vision 접근법 (A Computer Vision Approach for Identifying Acupuncture Points on the Face and Hand Using the MediaPipe Framework)

  • 하디;이명기;이병일
    • 한국정보처리학회:학술대회논문집
    • /
    • 한국정보처리학회 2023년도 추계학술발표대회
    • /
    • pp.563-565
    • /
    • 2023
  • Acupuncture and acupressure apply needles or pressure to anatomical points for therapeutic benefit. The over 350 mapped acupuncture points in the human body can each treat various conditions, but anatomical variations make precisely locating these acupoints difficult. We propose a computer vision technique using the real-time hand and face tracking capabilities of the MediaPipe framework to identify acupoint locations. Our model detects anatomical facial and hand landmarks, and then maps these to corresponding acupoint regions. In summary, our proposed model facilitates precise acupoint localization for self-treatment and enhances practitioners' abilities to deliver targeted acupuncture and acupressure therapies.

초음파 후방산란 신호와 합성곱 신경망을 이용한 점토 현탁액 자동 분류 시스템 (Automated classification of clay suspension using ultrasonic backscattered signal with convolution neural network)

  • 성영호 ;주인철;김장건 ;원종묵 ;임해균
    • 한국정보처리학회:학술대회논문집
    • /
    • 한국정보처리학회 2023년도 추계학술발표대회
    • /
    • pp.665-666
    • /
    • 2023
  • 미세 물질을 포함하고 있는 광산 폐기물의 디워터링 과정(dewatering process)은 작은 입자들의 침전속도가 낮기 때문에 시간이 오래 걸리고 어려운 과정이다. 따라서 광산 폐기물이 안정적으로 침전되었는지 확인하기 위해서 디워터링 과정을 연속적으로 모니터링하는 기술이 필요하다. 이 연구에서는 kaolinite, illite, bentonite 3 종류의 점토를 3 가지 농도(0.1g/L, 1g/L, 5g/L)로 나눠서 초음파 음향 감지를 이용해 후방산란 신호를 측정했다. 그리고 측정된 신호를 활용하여 합성곱 신경망(CNN) 모델을 개발하여 점토의 분류 모델을 만드는 연구를 수행했다. 본 연구에서 보여준 CNN 의 높은 정확도는 광산 폐기물의 디워터링 과정에서 미세 광물과 미세 농도 분류 모니터링에 적합한 저렴하고 측정하기 쉬운 음향 감지의 사용 가능성을 입증했다.

딥러닝을 활용한 3차원 초음파 파노라마 영상 복원 (3D Ultrasound Panoramic Image Reconstruction using Deep Learning)

  • 이시열;김선호;이동언;박춘수;김민우
    • 대한의용생체공학회:의공학회지
    • /
    • 제44권4호
    • /
    • pp.255-263
    • /
    • 2023
  • Clinical ultrasound (US) is a widely used imaging modality with various clinical applications. However, capturing a large field of view often requires specialized transducers which have limitations for specific clinical scenarios. Panoramic imaging offers an alternative approach by sequentially aligning image sections acquired from freehand sweeps using a standard transducer. To reconstruct a 3D volume from these 2D sections, an external device can be employed to track the transducer's motion accurately. However, the presence of optical or electrical interferences in a clinical setting often leads to incorrect measurements from such sensors. In this paper, we propose a deep learning (DL) framework that enables the prediction of scan trajectories using only US data, eliminating the need for an external tracking device. Our approach incorporates diverse data types, including correlation volume, optical flow, B-mode images, and rawer data (IQ data). We develop a DL network capable of effectively handling these data types and introduce an attention technique to emphasize crucial local areas for precise trajectory prediction. Through extensive experimentation, we demonstrate the superiority of our proposed method over other DL-based approaches in terms of long trajectory prediction performance. Our findings highlight the potential of employing DL techniques for trajectory estimation in clinical ultrasound, offering a promising alternative for panoramic imaging.

비대면 원격진단을 위한 디지털 검이경 청진기 헬스케어 플랫폼 개발 (Development of a Digital Otoscope-Stethoscope Healthcare Platform for Telemedicine)

  • 최수영;이학;박찬용;주수빈;권오원;이동규
    • 대한의용생체공학회:의공학회지
    • /
    • 제45권3호
    • /
    • pp.109-117
    • /
    • 2024
  • We developed a device that integrates digital otoscope and stethoscope for telemedicine. The integrated device was utilized for the collection of tympanic membrane images and cardiac auscultation data. Data accumulated on the platform server can support real-time diagnosis of heart and eardrum diseases using artificial intelligence. Public data from Kaggle were used for deep learning. After comparing with various deep learning models, the MobileNetV2 model showed superior performance in analyzing tympanic membrane data, and the VGG16 model excelled in analyzing cardiac data. The classification algorithm achieved an accuracy of 89.9% for eardrums data and 100% for heart sound data. These results demonstrate the possibility of diagnosing diseases without the limitations of time and space by using this platform.

초음파 영상 특성을 이용한 실시간 초음파 영역 추출방법 (Real-time Ultrasound Contexts Segmentation Based on Ultrasound Image Characteristic)

  • 최성진;이민우
    • 대한의용생체공학회:의공학회지
    • /
    • 제40권5호
    • /
    • pp.179-188
    • /
    • 2019
  • 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.

관형 요도 조직 대상 내시경적 레이저 조사 조건 연구 (Endoscopic Laser Irradiation Condition of Urethra in Tubular Structure)

  • 신화랑;임성희;이예찬;강현욱
    • 대한의용생체공학회:의공학회지
    • /
    • 제44권1호
    • /
    • pp.85-91
    • /
    • 2023
  • Stress urinary incontinence (SUI) occurs when abdominal pressure increases, such as sneezing, exercising, and laughing. Surgical and non-surgical treatments are the common methods of SUI treatment; however, the conventional treatments still require continuous and invasive treatment. Laser have been used to treat SUI, but excessive temperature increase often causes thermal burn on urethra tissue. Therefore, the optimal conditions must be considered to minimize the thermal damage for the laser treatment. The current study investigated the feasibility of the laser irradiation condition for SUI treatment using non-ablative 980 nm laser from a safety perspective through numerical simulations. COMSOL Multiphysics was used to analyze the numerical simulation model. The Pennes bioheat equation with the Beer's law was used to confirm spatio-temporal temperature distributions, and Arrhenius equation defined the thermal damage caused by the laser-induced heat. Ex vivo porcine urethral tissue was tested to validate the extent of both temperature distribution and thermal damage. The temperature distribution was symmetrical and uniformly observed in the urethra tissue. A muscle layer had a higher temperature (28.3 ℃) than mucosal (23.4 ℃) and submucosal layers (25.5 ℃). MT staining revealed no heat-induced collagen and muscle damage. Both control and treated groups showed the equivalent thickness and area of the urethral mucosal layer. Therefore, the proposed numerical simulation can predict the appropriate irradiation condition (20 W for 15 s) for the SUI treatment with minimal temperature-induced tissue.

세포외기질(ECM) 생체소재 기반 필러 개발 연구 (Development of Extracellular Matrix (ECM) based Dermal Filler)

  • 김나현;박상혁
    • 대한의용생체공학회:의공학회지
    • /
    • 제40권4호
    • /
    • pp.137-142
    • /
    • 2019
  • Numerous efforts are being made to develop an ideal dermal filler that should be bio-compatibility, non-immunogenicity, long-lasting and biodegradable without a toxic secretion. Biomaterials of dermal fillers are hyaluronic acid filler, calcium filler, PMMA filler and collagen filler depending on the ingredient. Although hyaluronic acid (HA) is most widely used, it has shortages such as short shelf life and low mechanical strength compare to extracellular matrix (ECM). The cartilage ECM composed of collagen type II, proteoglycans, glycosaminoglycans (GAGs) and in a minor part with glycoproteins. In this study, we developed a cartilage ECM injectable filler capable of improving biocompatibility and longevity compared with hyaluronic acid (HA) fillers. The ECM hydrogel was cross-linked by the reaction of N-(3-Dimethylaminopropyl)-N'-ethylcarbodiimide hydrochloride (EDC)/N-hydroxysuccinimide (NHS) for mechanical enhancement. Prepared ECM filler was compared with cross-linked HA by butanediol diglycidyle ether (BDDE), which is the most widely used natural polymers for dermal filler. In the results, the articular cartilage ECM hydrogel has great potential as a dermal filler to improve the biophysical and biological performance.

사용자 중심의 의료기기 광고를 위한 기술문서 심사 변경의 새로운 정책 연구 (A New Policy Study on Technical Document Review Changes and User-Centric Medical Device Advertising)

  • 안대익;류규하
    • 대한의용생체공학회:의공학회지
    • /
    • 제42권1호
    • /
    • pp.7-17
    • /
    • 2021
  • In the case of domestic medical device advertisements, it is possible to proceed with the advertisement after medical device certification, and pre-deliberation is possible based on the medical device technical document. However, there are some medical device advertisements that stakeholders in administrative procedures have no choice but to misunderstand in customs and laws that do not consider users. In addition, medical equipment and the pre-deliberation system were judged to be unconstitutional, and unconstitutional decisions were made in accordance with the principle of prohibiting pre-censorship based on the Constitution. This is because in domestic medical device advertisements, structural contradictions and user damage occur in the central structure of each stakeholder. It is necessary to reestablish stakeholder relationships, increase water solubility from customs and laws, and seek new policy proposals. In this study, we reestablish relationships with stakeholders by applying the Autopoiesis theory, and present the grounds and directions that can prevent hype and misidentified advertisements through the establishment of user-centered policies, and the measures to be taken by the Constitutional Court unconstitutional decision.