• Title/Summary/Keyword: Image-guided

Search Result 381, Processing Time 0.021 seconds

A Study on the Additional Absorbed Dose of Normal Tissues by Image Guided Radiation Therapy(IGRT) (영상유도 방사선 치료(IGRT)에 따른 정상 조직의 추가 피폭에 대한 연구)

  • Kim, Gha-Jung;Ryu, Jun-Min;Choi, Jun-Gu;Hong, Dong-Hee
    • The Journal of the Korea Contents Association
    • /
    • v.16 no.1
    • /
    • pp.75-81
    • /
    • 2016
  • The recent radiation therapy field can provide treatment which guarantees a high degree of accuracy, due to patient set-up using various image guided radiation therapy(IGRT) instruments. But the additional absorbed dose to patient's normal tissues is increasing. Therefore, this study measured the absorbed dose to surrounding normal tissues which is caused by patient set-up using OBI, CBCT, ExacTrac, among various IGRT instruments. The absorbed dose to the head, the chest, the abdomen, and the pelvis from CBCT was 12.57 mGy, 20.82 mGy, 82.93 mGy, and 52.70 mGy, respectively. Also, the absorbed dose from OBI and ExacTrac ranged from 0.76 to 8.58 mGy and from 0.14 to 0.63 mGy, respectively. As a result, CBCT's absorbed dose was far higher than other instruments. CBCT's surface dose was far higher than others, too, but OBI's entrance skin dose was almost the same as CBCT's.

Surgical Management Options for Trigeminal Neuralgia

  • Lunsford, L. Dade;Niranjan, Ajay;Kondziolka, Douglas
    • Journal of Korean Neurosurgical Society
    • /
    • v.41 no.6
    • /
    • pp.359-366
    • /
    • 2007
  • Trigeminal neuralgia is a condition associated with severe episodic lancinating facial pain subject to remissions and relapses. Trigeminal neuralgia is often associated with blood vessel cross compression of the root entry zone or more rarely with demyelinating diseases and occasionally with direct compression by neoplasms of the posterior fossa. If initial medical management fails to control pain or is associated with unacceptable side effects, a variety of surgical procedures offer the hope for long-lasting pain relief or even cure. For patients who are healthy without significant medical co-morbidities, direct microsurgical vascular decompression [MVD] offers treatment that is often definitive. Other surgical options are effective for elderly patients not suitable for MVD. Percutaneous retrogasserian glycerol rhizotomy is a minimally invasive technique that is based on anatomic definition of the trigeminal cistern followed by injection of anhydrous glycerol to produce a weak neurolytic effect on the post-ganglionic fibers. Other percutaneous management strategies include radiofrequency rhizotomy and balloon compression. More recently, stereotactic radiosurgery has been used as a truly minimally invasive strategy. It also is anatomically based using high resolution MRI to define the retrogasserian target. Radiosurgery provides effective symptomatic relief in the vast majority of patients, especially those who have never had prior surgical procedures. For younger patients, we recommend microvascular decompression. For patients with severe exacerbations of their pain and who need rapid response to treatment, we suggest glycerol rhizotomy. For other patients, gamma knife radiosurgery represents an effective management strategy with excellent preservation of existing facial sensation.

A Novel Image Dehazing Algorithm Based on Dual-tree Complex Wavelet Transform

  • Huang, Changxin;Li, Wei;Han, Songchen;Liang, Binbin;Cheng, Peng
    • KSII Transactions on Internet and Information Systems (TIIS)
    • /
    • v.12 no.10
    • /
    • pp.5039-5055
    • /
    • 2018
  • The quality of natural outdoor images captured by visible camera sensors is usually degraded by the haze present in the atmosphere. In this paper, a fast image dehazing method based on visible image and near-infrared fusion is proposed. In the proposed method, a visible and a near-infrared (NIR) image of the same scene is fused based on the dual-tree complex wavelet transform (DT-CWT) to generate a dehazed color image. The color of the fusion image is regulated through haze concentration estimated by dark channel prior (DCP). The experiment results demonstrate that the proposed method outperforms the conventional dehazing methods and effectively solves the color distortion problem in the dehazing process.

NIR Fluorescence Imaging Systems with Optical Packaging Technology

  • Yang, Andrew Wootae;Cho, Sang Uk;Jeong, Myung Yung;Choi, Hak Soo
    • Journal of the Microelectronics and Packaging Society
    • /
    • v.21 no.4
    • /
    • pp.25-31
    • /
    • 2014
  • Bioimaging has advanced the field of nanomedicine, drug delivery, and tissue engineering by directly visualizing the dynamic mechanism of diagnostic agents or therapeutic drugs in the body. In particular, wide-field, planar, near-infrared (NIR) fluorescence imaging has the potential to revolutionize human surgery by providing real-time image guidance to surgeons for target tissues to be resected and vital tissues to be preserved. In this review, we introduce the principles of NIR fluorescence imaging and analyze currently available NIR fluorescence imaging systems with special focus on optical source and packaging. We also introduce the evolution of the FLARE intraoperative imaging technology as an example for image-guided surgery.

Image-guided Stereotactic Neurosurgery: Practices and Pitfalls

  • Jung, Na Young;Kim, Minsoo;Kim, Young Goo;Jung, Hyun Ho;Chang, Jin Woo;Park, Yong Gou;Chang, Won Seok
    • Journal of International Society for Simulation Surgery
    • /
    • v.2 no.2
    • /
    • pp.58-63
    • /
    • 2015
  • Image-guided neurosurgery (IGN) is a technique for localizing objects of surgical interest within the brain. In the past, its main use was placement of electrodes; however, the advent of computed tomography has led to a rebirth of IGN. Advances in computing techniques and neuroimaging tools allow improved surgical planning and intraoperative information. IGN influences many neurosurgical fields including neuro-oncology, functional disease, and radiosurgery. As development continues, several problems remain to be solved. This article provides a general overview of IGN with a brief discussion of future directions.

An Image-guided Radiosurgery for the Treatment of Metastatic Bone Tumors using the CyberKnife Robotic System

  • Cho, Chul-Koo
    • The Journal of the Korean bone and joint tumor society
    • /
    • v.13 no.1
    • /
    • pp.14-21
    • /
    • 2007
  • Bone is a common site for metastatic spread from many kinds of malignancies. The morbidity associated with this metastatic spread can be significant, including severe pain. When it comes to spinal metastasis, occupying nearly 40% of skeletal metastases, the risks of complications, such as vertebral body collapse, nerve root impingement, or spinal cord compression, are also significant. Because of the necessity of preserving the integrity of the spinal column and the proximity of critical structures, surgical treatment has limitations when durable local control is desired. Radiotherapy, therefore, is often used as an adjunct treatment or as a sole treatment. A considerable limitation of standard radiotherapy is the reported recurrence rate or ineffective palliation of pain, either clinically or symptomatically. This may be due to limited radiation doses to tumor itself because of the proximity of critical structures. CyberKnife is an image-guided robotic radiosurgical system. The image guidance system includes a kilovoltage X-ray imaging source and amorphous silica detectors. The radiation delivery device is a mobile X-band linear accelerator (6 MV) mounted on a robotic arm. Highly conformal fields and hypofractionated radiotherapy schedules are increasingly being used as a means to achieve biologic dose escalation for body tumors. Therefore, we can give much higher doses to the targeted tumor volume with minimizing doses to the surrounding critical structures, resulting in more effective local control and less severe side effects, compared to conventional fractionated radiotherapy. A description of this technology and a review of clinical applications to bone metastases are detailed herein.

  • PDF

Evaluation of Denoising Filters Based on Edge Locations

  • Seo, Suyoung
    • Korean Journal of Remote Sensing
    • /
    • v.36 no.4
    • /
    • pp.503-513
    • /
    • 2020
  • This paper presents a method to evaluate denoising filters based on edge locations in their denoised images. Image quality assessment has often been performed by using structural similarity (SSIM). However, SSIM does not provide clearly the geometric accuracy of features in denoised images. Thus, in this paper, a method to localize edge locations with subpixel accuracy based on adaptive weighting of gradients is used for obtaining the subpixel locations of edges in ground truth image, noisy images, and denoised images. Then, this paper proposes a method to evaluate the geometric accuracy of edge locations based on root mean squares error (RMSE) and jaggedness with reference to ground truth locations. Jaggedness is a measure proposed in this study to measure the stability of the distribution of edge locations. Tested denoising filters are anisotropic diffusion (AF), bilateral filter, guided filter, weighted guided filter, weighted mean of patches filter, and smoothing filter (SF). SF is a simple filter that smooths images by applying a Gaussian blurring to a noisy image. Experiments were performed with a set of simulated images and natural images. The experimental results show that AF and SF recovered edge locations more accurately than the other tested filters in terms of SSIM, RMSE, and jaggedness and that SF produced better results than AF in terms of jaggedness.

Few-shot Aerial Image Segmentation with Mask-Guided Attention (마스크-보조 어텐션 기법을 활용한 항공 영상에서의 퓨-샷 의미론적 분할)

  • Kwon, Hyeongjun;Song, Taeyong;Lee, Tae-Young;Ahn, Jongsik;Sohn, Kwanghoon
    • Journal of Korea Multimedia Society
    • /
    • v.25 no.5
    • /
    • pp.685-694
    • /
    • 2022
  • The goal of few-shot semantic segmentation is to build a network that quickly adapts to novel classes with extreme data shortage regimes. Most existing few-shot segmentation methods leverage single or multiple prototypes from extracted support features. Although there have been promising results for natural images, these methods are not directly applicable to the aerial image domain. A key factor in few-shot segmentation on aerial images is to effectively exploit information that is robust against extreme changes in background and object scales. In this paper, we propose a Mask-Guided Attention module to extract more comprehensive support features for few-shot segmentation in aerial images. Taking advantage of the support ground-truth masks, the area correlated to the foreground object is highlighted and enables the support encoder to extract comprehensive support features with contextual information. To facilitate reproducible studies of the task of few-shot semantic segmentation in aerial images, we further present the few-shot segmentation benchmark iSAID-, which is constructed from a large-scale iSAID dataset. Extensive experimental results including comparisons with the state-of-the-art methods and ablation studies demonstrate the effectiveness of the proposed method.

AdaMM-DepthNet: Unsupervised Adaptive Depth Estimation Guided by Min and Max Depth Priors for Monocular Images

  • Bello, Juan Luis Gonzalez;Kim, Munchurl
    • Proceedings of the Korean Society of Broadcast Engineers Conference
    • /
    • 2020.11a
    • /
    • pp.252-255
    • /
    • 2020
  • Unsupervised deep learning methods have shown impressive results for the challenging monocular depth estimation task, a field of study that has gained attention in recent years. A common approach for this task is to train a deep convolutional neural network (DCNN) via an image synthesis sub-task, where additional views are utilized during training to minimize a photometric reconstruction error. Previous unsupervised depth estimation networks are trained within a fixed depth estimation range, irrespective of its possible range for a given image, leading to suboptimal estimates. To overcome this suboptimal limitation, we first propose an unsupervised adaptive depth estimation method guided by minimum and maximum (min-max) depth priors for a given input image. The incorporation of min-max depth priors can drastically reduce the depth estimation complexity and produce depth estimates with higher accuracy. Moreover, we propose a novel network architecture for adaptive depth estimation, called the AdaMM-DepthNet, which adopts the min-max depth estimation in its front side. Intensive experimental results demonstrate that the adaptive depth estimation can significantly boost up the accuracy with a fewer number of parameters over the conventional approaches with a fixed minimum and maximum depth range.

  • PDF

Optimizing Imaging Conditions in Digital Tomosynthesis for Image-Guided Radiation Therapy (영상유도 방사선 치료를 위한 디지털 단층영상합성법의 촬영조건 최적화에 관한 연구)

  • Youn, Han-Bean;Kim, Jin-Sung;Cho, Min-Kook;Jang, Sun-Young;Song, William Y.;Kim, Ho-Kyung
    • Progress in Medical Physics
    • /
    • v.21 no.3
    • /
    • pp.281-290
    • /
    • 2010
  • Cone-beam digital tomosynthesis (CBDT) has greatly been paid attention in the image-guided radiation therapy because of its attractive advantages such as low patient dose and less motion artifact. Image quality of tomograms is, however, dependent on the imaging conditions such as the scan angle (${\beta}_{scan}$) and the number of projection views. In this paper, we describe the principle of CBDT based on filtered-backprojection technique and investigate the optimization of imaging conditions. As a system performance, we have defined the figure-of-merit with a combination of signal difference-to-noise ratio, artifact spread function and floating-point operations which determine the computational load of image reconstruction procedures. From the measurements of disc phantom, which mimics an impulse signal and thus their analyses, it is concluded that the image quality of tomograms obtained from CBDT is improved as the scan angle is wider than 60 degrees with a larger step scan angle (${\Delta}{\beta}$). As a rule of thumb, the system performance is dependent on $\sqrt{{\Delta}{\beta}}{\times}{\beta}^{2.5}_{scan}$. If the exact weighting factors could be assigned to each image-quality metric, we would find the better quantitative imaging conditions.