基于C型臂手术导航系统的相关问题

基于C形臂的手术导航是一种典型的计算机辅助手术技术,其以XR II图像作为载体,通过虚拟显示手术实体引导医生完成高质量手术.文章对基于C形臂手术导航技术诸多方面的问题进行了探讨,其中包括系统工作原理、关键技术、组成部件、主要适用领域及优势与不足等.在此基础上,还对基于C形臂手术导航技术的发展走向进行了讨论.     

Combined video tracking and image-video registration for continuous bronchoscopic guidance

Objective

Three-dimensional (3D) computed-tomography (CT) images and bronchoscopy are commonly used tools for the assessment of lung cancer. Before bronchoscopy, the physician first examines a 3D CT chest image to select pertinent diagnostic sites and to ascertain possible routes through the airway tree leading to each site. Next, during bronchoscopy, the physician maneuvers the bronchoscope through the airways, basing navigation decisions on the live bronchoscopic video, to reach each diagnostic site. Unfortunately, no direct link exists between the 3D CT image data and bronchoscopic video. This makes bronchoscopy difficult to perform successfully. Existing methods for the image-based guidance of bronchoscopy, either only involve single-frame registration or operate at impractically slow frame rates. We describe a method that combines the 3D CT image data and bronchoscopic video to enable continuous bronchoscopic guidance.

Methods

The method interleaves periodic CT-video registration with bronchoscopic video motion tracking. It begins by using single-frame CT-video registration to register the “Real World” of the bronchoscopic video and the “Virtual World” of the CT-based endoluminal renderings. Next, the method uses an optical-flow-based approach to track bronchoscope movement for a fixed number of video frames and also simultaneously updates the virtual-world position. This process of registration and tracking repeats as the bronchoscope moves.

Results

The method operates robustly over a variety ofphantom and human cases. It typically performs successfully for over 150 frames and through multiple airway generations. In our tests, the method runs at a rate of up to seven frames per second. We have integrated the method into a complete system for the image-based planning and guidance of bronchoscopy.

Conclusion

The method performs over an order of magnitude faster than previously proposed image-based bronchoscopy guidance methods. Software optimization and a modest hardware improvement could enable real-time performance.     

MR image overlay guidance: system evaluation for preclinical use

Purpose

A clinical augmented reality guidance system was developed for MRI-guided musculoskeletal interventions Magnetic Resonance Image Overlay System (MR-IOS). The purpose of this study was to assess MRI compatibility, system accuracy, technical efficacy, and operator performance of the MR-IOS.

Methods and materials

The impact of the MR-IOS on the MR environment was assessed by measuring image quality with signal-to-noise ratio (SNR) and signal intensity uniformity with the system in various on/off states. The system accuracy was assessed with an in-room preclinical experiment by performing 62 needle insertions on a spine phantom by an expert operator measuring entry, depth, angle, and target errors. Technical efficacy and operator performance were tested in laboratory by running an experiment with 40 novice operators (20 using freehand technique versus 20 MR-IOS-guided) with each operator inserting 10 needles into a geometric phantom. Technical efficacy was measured by comparing the success rates of needle insertions between the two operator groups. Operator performance was assessed by comparing total procedure times, total needle path distance, presumed tissue damage, and speed of individual insertions between the two operator groups.

Results

The MR-IOS maximally altered SNR by 2% with no perceptible change in image quality or uniformity. Accuracy assessment showed mean entry error of 1.6 ± 0.6 mm, depth error of 0.7 ± 0.5 mm, angle error of 1.5 ± 1.1°, and target error of 1.9 ± 0.8 mm. Technical efficacy showed a statistically significant difference (p = 0.031) between success rates (freehand 35.0% vs. MR-IOS 80.95%). Operator performance showed: mean total procedure time of 40.3 ± 4.4 (s) for freehand and 37.0 ± 3.7 (s) for MR-IOS (p = 0.584), needle path distances of 152.6 ± 15.0 mm for freehand and 116.9 ± 8.7 mm for MR-IOS (p = 0.074), presumed tissue damage of 7,417.2 ± 955.6 mm² for freehand and 6062.2 ± 678.5 mm² for MR-IOS (p = 0.347), and speed of insertion 5.9 ± 0.4 mm/s for freehand and 4.3 ± 0.3 mm/s for MR-IOS (p = 0.003).

Conclusion

The MR-IOS is compatible within a clinical MR imaging environment, accurate for needle placement, technically efficacious, and improves operator performance over the unassisted insertion technique. The MR-IOS was found to be suitable for further testing in a clinical setting.     

基于C型臂手术导航技术的XRⅡ图像中标志物识别及数据提取

XRⅡ图像中标志物的识别及数据提取是基于C型臂手术导航关键技术之一.现有方法可靠性差,检测精度低.文章提出一种混合标志物检测算法,首先通过一种改进CHT法获取参数空间,并获取其横切面二值化图像:而后进行连通分量分析,识别出其中的圆形体并提取其面积及中心坐标数据.改进CHT对掩模及积分算子进行了重新定义;连通分量分析则采用一种新的圆形测度.实验结果表明,所提算法具有更高检测率、检测精度及可靠性.     

Semi-supervised task-driven data augmentation for medical image segmentation

Supervised learning-based segmentation methods typically require a large number of annotated training data to generalize well at test time. In medical applications, curating such datasets is not a favourable option because acquiring a large number of annotated samples from experts is time-consuming and expensive. Consequently, numerous methods have been proposed in the literature for learning with limited annotated examples. Unfortunately, the proposed approaches in the literature have not yet yielded significant gains over random data augmentation for image segmentation, where random augmentations themselves do not yield high accuracy. In this work, we propose a novel task-driven data augmentation method for learning with limited labeled data where the synthetic data generator, is optimized for the segmentation task. The generator of the proposed method models intensity and shape variations using two sets of transformations, as additive intensity transformations and deformation fields. Both transformations are optimized using labeled as well as unlabeled examples in a semi-supervised framework. Our experiments on three medical datasets, namely cardiac, prostate and pancreas, show that the proposed approach significantly outperforms standard augmentation and semi-supervised approaches for image segmentation in the limited annotation setting.The code is made publicly available at https://github.com/krishnabits001/task_driven_data_augmentation.     

Operative ultrasound guidance for various surgical procedures

Although percutaneous ultrasound-guided technique is currently a common practice, the use of ultrasound for the purpose of guidance during surgery has not been widely practiced. Over a period of 10 years, we performed operative ultrasonography in 2,314 operations. In 321 of these operations, operative ultrasound guidance was performed for direct assistance of various surgical procedures, particularly during operations on the brain and spinal cord, liver, pancreas, and kidney. Procedures guided by operative ultrasound were classified into the following categories: intraoperative needle placement for fluid aspiration (n = 38), agent injection (n = 14), catheter introduction (n = 27), biopsy (n = 57), surgical tissue dissection for incision (n = 48), resection (n = 82) of organs, and extraction (n = 55) of stones or foreign bodies. Operative ultrasound guidance facilitates various surgical procedures and is considered a useful modality for reducing operative complications, shortening operating time, performing otherwise impossible procedures, and, at times, developing new surgical operations.     

An image overlay system for medical data visualization

Image Overlay is a computer display technique which superimposes computer images over the user's direct view of the real world. The images are transformed in real-time so they appear to the user to be an integral part of the surrounding environment. By using Image Overlay with three-dimensional medical images such as CT reconstructions, a surgeon can visualize the data 'in-vivo', exactly positioned within the patient's anatomy, and potentially enhance the surgeon's ability to perform a complex procedure. This paper describes prototype Image Overlay systems and initial experimental results from those systems.     

一种应用于视皮质假体图像压缩及编码系统的设计

背景:目前,视皮质假体已成为视觉修复实现的主要方法之一,图像压缩在视皮质假体的前期图像处理过程中占有重要地位.目的:探讨从空域及亮度信息两个方面分别对图像信息进行压缩的方法.方法:选取哈尔小波基对原始图像进行空间分辨率的压缩,并采用多尺度小波变换的方法对空间频率信号进行合理选取,实现信息的进一步压缩.同时,结合视觉皮质放大的特性,通过模拟视网膜对图像的前期处理,建立了非均匀压缩模型,使得图像压缩过程更接近视觉处理过程.还对亮度信息进行压缩及编码,实现了图像信息最终的压缩编码.结果与结论:构建了基于数字信号处理器的前期图像压缩及编码系统,最终实现了在10*10的点阵图阵列中进行图像信息的表达.     

Real-time evaluation of an image analysis system for monitoring surgical hemoglobin loss

Monitoring blood loss is important for management of surgical patients. This study reviews a device (Triton) that uses computer analysis of a photograph to estimate hemoglobin (Hb) mass present on surgical sponges. The device essentially does what a clinician does when trying to make a visual estimation of blood loss by looking at a sponge, albeit with less subjective variation. The performance of the Triton system is reported upon in during real-time use in surgical procedures. The cumulative Hb losses estimated using the Triton system for 50 enrolled patients were compared with reference Hb measurements during the first quarter, half, three-quarters and full duration of the surgery. Additionally, the estimated blood loss (EBL) was calculated using the Triton measured Hb loss and compared with values obtained from both visual estimation and gravimetric measurements. Hb loss measured by Triton correlated with the reference method across the four measurement intervals. Bias remained low and increased from 0.1 g in the first quarter to 3.7 g at case completion. The limits of agreement remained narrow and increased proportionally from the beginning to the end of the cases, reaching a maximum range of ?15.3 to 22.7 g. The median (IQR) difference of EBL derived from the Triton system, gravimetric method and visual estimation versus the reference value were 13 (74), 389 (287), and 4 (230) mL, respectively. Use of the Triton system to measure Hb loss in real-time during surgery is feasible and accurate.     

Systems for tracking minimally invasive surgical instruments

Minimally invasive surgery (e.g. laparoscopy) requires special surgical skills, which should be objectively assessed. Several studies have shown that motion analysis is a valuable assessment tool of basic surgical skills in laparoscopy. However, to use motion analysis as the assessment tool, it is necessary to track and record the motions of laparoscopic instruments. This article describes the state of the art in research on tracking systems for laparoscopy. It gives an overview on existing systems, on how these systems work, their advantages, and their shortcomings. Although various approaches have been used, none of the tracking systems to date comes out as clearly superior. A great number of systems can be used in training environment only, most systems do not allow the use of real laparoscopic instruments, and only a small number of systems provide force feedback.     

Intra-operative 3D guidance and edema detection in prostate brachytherapy using a non-isocentric C-arm

PurposeBrachytherapy (radioactive seed insertion) has emerged as one of the most effective treatment options for patients with prostate cancer, with the added benefit of a convenient outpatient procedure. The main limitation in contemporary brachytherapy is faulty seed placement, predominantly due to the presence of intra-operative edema (tissue expansion). Though currently not available, the capability to intra-operatively monitor the seed distribution, can make a significant improvement in cancer control. We present such a system here.MethodsIntra-operative measurement of edema in prostate brachytherapy requires localization of inserted radioactive seeds relative to the prostate. Seeds were reconstructed using a typical non-isocentric C-arm, and exported to a commercial brachytherapy treatment planning system. Technical obstacles for 3D reconstruction on a non-isocentric C-arm include pose-dependent C-arm calibration; distortion correction; pose estimation of C-arm images; seed reconstruction; and C-arm to TRUS registration.ResultsIn precision-machined hard phantoms with 40–100 seeds and soft tissue phantoms with 45–87 seeds, we correctly reconstructed the seed implant shape with an average 3D precision of 0.35 mm and 0.24 mm, respectively. In a DoD Phase-1 clinical trial on six patients with 48–82 planned seeds, we achieved intra-operative monitoring of seed distribution and dosimetry, correcting for dose inhomogeneities by inserting an average of over four additional seeds in the six enrolled patients (minimum 1; maximum 9). Additionally, in each patient, the system automatically detected intra-operative seed migration induced due to edema (mean 3.84 mm, STD 2.13 mm, Max 16.19 mm).ConclusionsThe proposed system is the first of a kind that makes intra-operative detection of edema (and subsequent re-optimization) possible on any typical non-isocentric C-arm, at negligible additional cost to the existing clinical installation. It achieves a significantly more homogeneous seed distribution, and has the potential to affect a paradigm shift in clinical practice. Large scale studies and commercialization are currently underway.     

Selective image similarity measure for bronchoscope tracking based on image registration

We propose a selective method of measurement for computing image similarities based on characteristic structure extraction and demonstrate its application to flexible endoscope navigation, in particular to a bronchoscope navigation system. Camera motion tracking is a fundamental function required for image-guided treatment or therapy systems. In recent years, an ultra-tiny electromagnetic sensor commercially became available, and many image-guided treatment or therapy systems use this sensor for tracking the camera position and orientation. However, due to space limitations, it is difficult to equip the tip of a bronchoscope with such a position sensor, especially in the case of ultra-thin bronchoscopes. Therefore, continuous image registration between real and virtual bronchoscopic images becomes an efficient tool for tracking the bronchoscope. Usually, image registration is done by calculating the image similarity between real and virtual bronchoscopic images. Since global schemes to measure image similarity, such as mutual information, squared gray-level difference, or cross correlation, average differences in intensity values over an entire region, they fail at tracking of scenes where less characteristic structures can be observed. The proposed method divides an entire image into a set of small subblocks and only selects those in which characteristic shapes are observed. Then image similarity is calculated within the selected subblocks. Selection is done by calculating feature values within each subblock. We applied our proposed method to eight pairs of chest X-ray CT images and bronchoscopic video images. The experimental results revealed that bronchoscope tracking using the proposed method could track up to 1600 consecutive bronchoscopic images (about 50 s) without external position sensors. Tracking performance was greatly improved in comparison with a standard method utilizing squared gray-level differences of the entire images.     

质量追溯信息管理系统在手术器械安全管理中的应用

为探讨消毒供应可追溯管理系统在手术器械中的应用效果,规范手术器械管理流程,为控制医院感染、降低医疗成本提供科学的依据。通过扫描条码的形式,追踪器械在供应室从回收、清洗消毒、包装、灭菌到发放以及在手术室使用的整个过程。应用质量追溯信息管理系统后,手术器械灭菌合格率99.9%,不合格物品追回率100%。通过质量全程追溯管理保证了手术器械清洗消毒及灭菌质量,有效地避免了器械包下落不明难以查找的情况,提高了工作效率。     

Diverse data augmentation for learning image segmentation with cross-modality annotations

The dearth of annotated data is a major hurdle in building reliable image segmentation models. Manual annotation of medical images is tedious, time-consuming, and significantly variable across imaging modalities. The need for annotation can be ameliorated by leveraging an annotation-rich source modality in learning a segmentation model for an annotation-poor target modality. In this paper, we introduce a diverse data augmentation generative adversarial network (DDA-GAN) to train a segmentation model for an unannotated target image domain by borrowing information from an annotated source image domain. This is achieved by generating diverse augmented data for the target domain by one-to-many source-to-target translation. The DDA-GAN uses unpaired images from the source and target domains and is an end-to-end convolutional neural network that (i) explicitly disentangles domain-invariant structural features related to segmentation from domain-specific appearance features, (ii) combines structural features from the source domain with appearance features randomly sampled from the target domain for data augmentation, and (iii) train the segmentation model with the augmented data in the target domain and the annotations from the source domain. The effectiveness of our method is demonstrated both qualitatively and quantitatively in comparison with the state of the art for segmentation of craniomaxillofacial bony structures via MRI and cardiac substructures via CT.     

三维电解剖标测系统与CT影像融合指导心房颤动导管消融

背景:目前通常采用的肺静脉前庭定位方法主要有三维电解剖标测系统指导(CARTO)或与CT/核磁共振影像融合定位(CARTO-Merge)两种方法.理论上讲CARTO-Merge技术提供了更多的解剖细节,导航精确度更高,但其是否有利于提高房颤导管消融治疗的成功率及安全性仍有待临床观察评价.目的:验证三维电解剖标测系统联合CT影像融合在指导房颤导管消融中的作用.设计、时间及地点:对比观察,于2005-10/2007-05在首都医科大学附属北京安贞医院心内科完成.对象:选择进行环肺静脉前庭线性消融治疗的阵发性房颤患者93例.方法:试验分为2组,CARTO组50例,CARTO-Merge组43例,分别于CARTO系统及CARTO-Merge指导下行环肺静脉前庭线性消融,消融终点为肺静脉隔离.主要观察指标:比较两组操作时间,X射线照射时间,手术成功率及并发症等情况.结果:所有患者均实现消融终点,随访时间(12.6±2.9)个月,73例(78.5%)患者消融后3个月无房性心律失常复发.CARTO组X射线照射时间显著长于CARTO-Merge组(P<0.05),两组操作时间、消融时间、消融成功率及并发症比较差异无显著性意义(P>0.05).结论:采用单纯CARTO或联合CT影像融合技术指导的环肺静脉前庭消融均具有良好的临床疗效和安全性.但CT影像融合技术可更清楚展示心脏解剖,有利于肺静脉的准确定位,并显著缩短X射线透视时间.     

Systems for tracking minimally invasive surgical instruments.

Minimally invasive surgery (e.g. laparoscopy) requires special surgical skills, which should be objectively assessed. Several studies have shown that motion analysis is a valuable assessment tool of basic surgical skills in laparoscopy. However, to use motion analysis as the assessment tool, it is necessary to track and record the motions of laparoscopic instruments. This article describes the state of the art in research on tracking systems for laparoscopy. It gives an overview on existing systems, on how these systems work, their advantages, and their shortcomings. Although various approaches have been used, none of the tracking systems to date comes out as clearly superior. A great number of systems can be used in training environment only, most systems do not allow the use of real laparoscopic instruments, and only a small number of systems provide force feedback.     

An automated form of video image analysis applied to classification of movement disorders

Video image analysis is able to provide quantitative data on postural and movement abnormalities and thus has an important application in neurological diagnosis and management. The conventional techniques require patients to be videotaped while wearing markers in a highly structured laboratory environment. This restricts the utility of video in routine clinical practise. We have begun development of intelligent software which aims to provide a more flexible system able to quantify human posture and movement directly from whole-body images without markers and in an unstructured environment. The steps involved are to extract complete human profiles from video frames, to fit skeletal frameworks to the profiles and derive joint angles and swing distances. By this means a given posture is reduced to a set of basic parameters that can provide input to a neural network classifier. To test the system's performance we videotaped patients with dopa-responsive Parkinsonism and age-matched normals during several gait cycles, to yield 61 patient and 49 normal postures. These postures were reduced to their basic parameters and fed to the neural network classifier in various combinations. The optimal parameter sets (consisting of both swing distances and joint angles) yielded successful classification of normals and patients with an accuracy above 90%. This result demonstrated the feasibility of the approach. The technique has the potential to guide clinicians on the relative sensitivity of specific postural/gait features in diagnosis. Future studies will aim to improve the robustness of the system in providing accurate parameter estimates from subjects wearing a range of clothing, and to further improve discrimination by incorporating more stages of the gait cycle into the analysis.     

An automated form of video image analysis applied to classification of movement disorders

Video image analysis is able to provide quantitative data on postural and movement abnormalities and thus has an important application in neurological diagnosis and management. The conventional techniques require patients to be videotaped while wearing markers in a highly structured laboratory environment. This restricts the utility of video in routine clinical practise. We have begun development of intelligent software which aims to provide a more flexible system able to quantify human posture and movement directly from whole-body images without markers and in an unstructured environment. The steps involved are to extract complete human profiles from video frames, to fit skeletal frameworks to the profiles and derive joint angles and swing distances. By this means a given posture is reduced to a set of basic parameters that can provide input to a neural network classifier. To test the system's performance we videotaped patients with dopa-responsive Parkinsonism and age-matched normals during several gait cycles, to yield 61 patient and 49 normal postures. These postures were reduced to their basic parameters and fed to the neural network classifier in various combinations. The optimal parameter sets (consisting of both swing distances and joint angles) yielded successful classification of normals and patients with an accuracy above 90%. This result demonstrated the feasibility of the approach. The technique has the potential to guide clinicians on the relative sensitivity of specific postural/gait features in diagnosis. Future studies will aim to improve the robustness of the system in providing accurate parameter estimates from subjects wearing a range of clothing, and to further improve discrimination by incorporating more stages of the gait cycle into the analysis.     

An automated form of video image analysis applied to classification of movement disorders

Video image analysis is able to provide quantitative data on postural and movement abnormalities and thus has an important application in neurological diagnosis and management. The conventional techniques require patients to be videotaped while wearing markers in a highly structured laboratory environment. This restricts the utility of video in routine clinical practise. We have begun development of intelligent software which aims to provide a more flexible system able to quantify human posture and movement directly from whole-body images without markers and in an unstructured environment. The steps involved are to extract complete human profiles from video frames, to fit skeletal frameworks to the profiles and derive joint angles and swing distances. By this means a given posture is reduced to a set of basic parameters that can provide input to a neural network classifier. To test the system's performance we videotaped patients with dopa-responsive Parkinsonism and age-matched normals during several gait cycles, to yield 61 patient and 49 normal postures. These postures were reduced to their basic parameters and fed to the neural network classifier in various combinations. The optimal parameter sets (consisting of both swing distances and joint angles) yielded successful classification of normals and patients with an accuracy above 90%. This result demonstrated the feasibility of the approach. The technique has the potential to guide clinicians on the relative sensitivity of specific postural/gait features in diagnosis. Future studies will aim to improve the robustness of the system in providing accurate parameter estimates from subjects wearing a range of clothing, and to further improve discrimination by incorporating more stages of the gait cycle into the analysis.