Centre for Computer Graphics and Visualisation (CCGV)http://hdl.handle.net/10547/1322242024-03-29T04:41:25Z2024-03-29T04:41:25Z3D-holoscopic imaging: a new dimension to enhance Iimaging in minimally invasive therapy in urologic oncologyMakanjuola, Jonathan K.Aggoun, AmarSwash, MohammadGrange, Philippe C.R.Challacombe, BenjaminDasgupta, Prokarhttp://hdl.handle.net/10547/5935232020-04-23T07:36:10Z2013-05-01T00:00:00Z3D-holoscopic imaging: a new dimension to enhance Iimaging in minimally invasive therapy in urologic oncology
Makanjuola, Jonathan K.; Aggoun, Amar; Swash, Mohammad; Grange, Philippe C.R.; Challacombe, Benjamin; Dasgupta, Prokar
Background and Purpose: Existing imaging modalities of urologic pathology are limited by three-dimensional (3D) representation on a two-dimensional screen. We present 3D-holoscopic imaging as a novel method of representing Digital Imaging and Communications in Medicine data images taken from CT and MRI to produce 3D-holographic representations of anatomy without special eyewear in natural light. 3D-holoscopic technology produces images that are true optical models. This technology is based on physical principles with duplication of light fields. The 3D content is captured in real time with the content viewed by multiple viewers independently of their position, without 3D eyewear. Methods: We display 3D-holoscopic anatomy relevant to minimally invasive urologic surgery without the need for 3D eyewear. Results: The results have demonstrated that medical 3D-holoscopic content can be displayed on commercially available multiview auto-stereoscopic display. Conclusion: The next step is validation studies comparing 3D-Holoscopic imaging with conventional imaging.
2013-05-01T00:00:00ZThe refocusing distance of a standard plenoptic photographHahne, ChristopherAggoun, AmarVelisavljević, Vladanhttp://hdl.handle.net/10547/5569722020-12-15T12:25:04Z2015-06-12T00:00:00ZThe refocusing distance of a standard plenoptic photograph
Hahne, Christopher; Aggoun, Amar; Velisavljević, Vladan
In the past years, the plenoptic camera aroused an increasing interest in the field of computer vision. Its capability of capturing three-dimensional image data is achieved by an array of micro lenses placed in front of a traditional image sensor. The acquired light field data allows for the reconstruction of photographs focused at different depths. Given the plenoptic camera parameters, the metric distance of refocused objects may be retrieved with the aid of geometric ray tracing. Until now there was a lack of experimental results using real image data to prove this conceptual solution. With this paper, the very first experimental work is presented on the basis of a new ray tracing model approach, which considers more accurate micro image centre positions. To evaluate the developed method, the blur metric of objects in a refocused image stack is measured and compared with proposed predictions. The results suggest quite an accurate approximation for distant objects and deviations for objects closer to the camera device.
IEEE International Conference Paper
2015-06-12T00:00:00ZHealthcare-event driven semantic knowledge extraction with hybrid data repositoryYu, Hong QingZhao, XiaZhen, XinDong, FengLiu, EnjieClapworthy, Gordon J.http://hdl.handle.net/10547/3385102020-04-23T07:37:22Z2014-08-01T00:00:00ZHealthcare-event driven semantic knowledge extraction with hybrid data repository
Yu, Hong Qing; Zhao, Xia; Zhen, Xin; Dong, Feng; Liu, Enjie; Clapworthy, Gordon J.
In this paper, we introduce a Healthcare-Event (H-event) based knowledge extraction approach on a hybrid data repository. The repository collects (with individual user's permission) dynamic and large volume healthcare related data from various resources such as wearable sensors, social media Web APIs and our application itself. The proposed extraction approach relies on two data processing processes. One is the data integration process to dynamically retrieving the large data using public data service APIs. The first process also generates a set of big knowledge bases and stored in NoSQL storage. This paper will focus on the second extraction process that is the H-Event based ontological knowledge extraction for detecting and monitoring user's healthcare related situations, such as medical symptoms, treatments, conditions and daily activities from the NoSQL knowledge bases. The second process can be seen as post-processing step to detect more explicit healthcare knowledge about personalised health conditions and represent the knowledge using RDF formats in a semantic triple repository to enhance further data analytics.
2014-08-01T00:00:00ZSupport for the calculation of stent fatigue fracture in peripheral arteriesMcFarlane, Nigel J.B.Wei, HuiZhao, YoubingClapworthy, Gordon J.Testi, DeboraChiarini, Alessandrohttp://hdl.handle.net/10547/3385292020-04-23T07:37:13Z2013-01-01T00:00:00ZSupport for the calculation of stent fatigue fracture in peripheral arteries
McFarlane, Nigel J.B.; Wei, Hui; Zhao, Youbing; Clapworthy, Gordon J.; Testi, Debora; Chiarini, Alessandro
Vascular stenting is a medical intervention in which a wire mesh tube is inserted into an artery or vein to provide internal support. This is a safe and common procedure, but stents are now increasingly being deployed in peripheral locations, such as the femoral artery, as part of a procedure called Peripheral Vascular Angioplasty (PVA). Stents in such locations are subject to cyclic bending, and are therefore at risk of fatigue fracture. This paper describes the work of the RT3S project, which brings together stent modelling, surgical simulation and risk calculation for surgical planning. This will allow the clinical user to interactively assess different stent models and deployment options for breakage risk. In the RT3S system, models of several commercial models of self-expanding stent are available for simulation. The placement of the stent in the vessel and the withdrawal of the catheter sheath to expand the stent are visualised. A simplex control mesh is used to guide the deformation of the stent from its compressed start configuration to its expanded final position. The fracture risk for the given model and its patient-specific final position is precomputed using the response surfaces methodology.
2013-01-01T00:00:00Z