Image guided surgery through spatio-temporal signal amplification

通过时空信号放大进行图像引导手术

• 批准号: EP/N013220/1
• 负责人: Danail Stoyanov
• 金额: $ 12.52万
• 依托单位: University College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2016
• 资助国家: 英国
• 起止时间: 2016 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=EP%2FN013220%2F1
• 关键词: Image; guided; surgery; through; spatio

Through advances in instrumentation and high resolution digital video, surgical techniques are increasingly becoming more minimally invasive. Reducing the access trauma of surgery has many advantages for the patient such as reduced hospitalisation, scarring, co-morbidity and post-operative pain. However, limiting the surgeon's access to the surgical site inevitably increases the complexity of operations. Clinically, it is crucial to enhance visualisation during minimally invasive surgery and in particular to enable the surgeon to see structures underneath the exposed organ surface and to observe the functional characteristics of tissues. The availability of this information in real-time during surgery can assist the surgeon to prevent damage to critical anatomical structures and to preserve the viability of healthy tissues. Information about the location of blood vessels is actually inherently embedded in the endoscopic video signal from minimally invasive surgery in the form of motion. This can be observed easily when the vessel is large and near the tissue's surface. However, when the vessel is small and embedded within the tissue, the motion may be very subtle and not naturally visible by the naked eye because the human visual system is tuned to specific frequencies and motion amplitudes. Similar variations are present in the radiometric channels of endoscopic video, where colour fluctuations are surrogate measures of changes in tissue perfusion linked to the cardiac cycle. These subtle spatio-temporal video variations can be computationally detected and measured which constitutes the focus of the proposed project. The difficulty in exposing subtle variations in endoscopic video is that the surgical site is highly deformable and dynamic, which typically obscures the location of sub-surface vessels. To compensate for large scene dynamics, we will use a combination of registration and tracking techniques that temporally align specific regions of tissue. Once small variations have been identified, observations from different angles acquired either by a stereo endoscope or by a moving device will facilitate the localisation of vessels under the tissue. Mathematically, the theory of sparsity regularization and non-smooth regularisation will be exploited to solve for the vessel position leveraging existing research in tomography imaging e.g. using non-convex penalties and adaptive algorithms.The computational techniques to be developed, in the form of inverse problems for recovering and localising the source of subtle motion or colour variations, have wide applicability to many image and vision computing problems. In particular, applications where large dynamic effects need to be considered and removed apriori and where the problem is under determined due to the complexity of the structures under investigation.

随着器械和高分辨率数字视频的进步，外科技术正变得越来越微创。减少手术的入路创伤对患者有许多好处，如减少住院、减少疤痕、减少并发症和术后疼痛。然而，限制外科医生进入手术现场不可避免地增加了手术的复杂性。在临床上，在微创手术中加强可视化是至关重要的，尤其是使外科医生能够看到暴露的器官表面下的结构和观察组织的功能特征。在手术过程中实时获得这些信息可以帮助外科医生防止对关键解剖结构的损害，并保护健康组织的生存能力。有关血管位置的信息实际上以运动的形式嵌入到来自微创手术的内窥镜视频信号中。当血管较大且靠近组织表面时，很容易观察到这一点。然而，当血管很小并嵌入组织中时，运动可能非常微妙，肉眼无法自然看到，因为人类的视觉系统会调整到特定的频率和运动幅度。在内窥镜视频的辐射通道中也存在类似的变化，其中颜色波动是与心脏周期相关的组织灌注量变化的替代测量。这些细微的时空视频变化可以通过计算来检测和测量，这构成了拟议项目的重点。在内窥镜视频中曝光细微变化的困难在于手术部位高度变形和动态，这通常会模糊表面下血管的位置。为了补偿大场景动态，我们将使用配准和跟踪技术的组合，以在时间上对齐组织的特定区域。一旦识别出微小的变化，通过立体内窥镜或移动设备从不同角度获得的观察将有助于组织下血管的定位。在数学上，将利用稀疏正则化和非光滑正则化理论来利用断层成像中的现有研究来求解血管位置，例如使用非凸罚函数和自适应算法。将要开发的计算技术以反问题的形式来恢复和定位细微运动或颜色变化的来源，对许多图像和视觉计算问题具有广泛的适用性。特别是，需要事先考虑和消除大的动力效应的应用，以及由于所研究的结构的复杂性而无法确定问题的应用。

项目成果

Combined 2D and 3D tracking of surgical instruments for minimally invasive and robotic-assisted surgery.

• DOI: 10.1007/s11548-016-1393-4
• 发表时间: 2016-06
• 期刊: International journal of computer assisted radiology and surgery
• 影响因子: 3
• 作者: Du X;Allan M;Dore A;Ourselin S;Hawkes D;Kelly JD;Stoyanov D
• 通讯作者: Stoyanov D

HAPNet: hierarchically aggregated pyramid network for real-time stereo matching

• DOI: 10.1080/21681163.2020.1835561
• 发表时间: 2020-11-26
• 期刊: COMPUTER METHODS IN BIOMECHANICS AND BIOMEDICAL ENGINEERING-IMAGING AND VISUALIZATION
• 影响因子: 1.6
• 作者: Brandao, Patrick;Psychogyios, Dimitris;Janatka, Mirek
• 通讯作者: Janatka, Mirek

Refractive Structure-from-Motion Through a Flat Refractive Interface

• DOI: 10.1109/iccv.2017.568
• 发表时间: 2017-10
• 期刊: 2017 IEEE International Conference on Computer Vision (ICCV)
• 作者: F. Chadebecq;F. Vasconcelos;G. Dwyer;Rene M. Lacher;S. Ourselin;Tom Kamiel Magda Vercauteren;D. Stoyanov-D.-S

Robust Catheter and Guidewire Tracking Using B-Spline Tube Model and Pixel-Wise Posteriors

• DOI: 10.1109/lra.2016.2517821
• 发表时间: 2016-01-01
• 期刊: IEEE ROBOTICS AND AUTOMATION LETTERS
• 影响因子: 5.2
• 作者: Chang, Ping-Lin;Rolls, Alexander;Stoyanov, Danail
• 通讯作者: Stoyanov, Danail

Spectral Imaging Of Thermal Damage Induced During Microwave Ablation In The Liver.

肝脏微波消融过程中引起的热损伤的光谱成像。

• DOI: 10.1109/embc.2018.8512901
• 发表时间: 2018
• 期刊: Annual International Conference of the IEEE Engineering in Medicine and Biology Society. IEEE Engineering in Medicine and Biology Society. Annual International Conference
• 作者: Clancy NT