1,720,986 research outputs found
Registration of medical images for applications in minimally invasive procedures
Full text linkIl punto di partenza di questa tesi è l'analisi dei metodi allo stato dell'arte di registrazione delle immagini mediche per verificare se sono adatti ad essere utilizzati per assistere il medico durante una procedura minimamente invasiva , ad esempio una procedura percutanea eseguita manualmente o un intervento teleoperato eseguito per mezzo di un robot .
La prima conclusione è che, anche se ci sono tanti lavori dedicati allo sviluppo di algoritmi di registrazione da applicare nel contesto medico, la maggior parte di essi non sono stati progettati per essere utilizzati nello scenario della sala operatoria (OR) anche perché, rispetto ad altre applicazioni , OR richiede anche la validazione, prestazioni in tempo reale e la presenza di altri strumenti .
Gli algoritmi allo stato dell'arte sono basati su un iterazione in tre fasi : ottimizzazione - trasformazione - valutazione della somiglianza delle immagini registrate.
In questa tesi, studiamo la fattibilità dell'approccio in tre fasi per applicazioni OR, mostrando i limiti che tale approccio incontra nelle applicazioni che stiamo considerando. Verrà dimostrato come un metodo semplice si potrebbe utilizzare nella OR. Abbiamo poi sviluppato una teoria che è adatta a registrare grandi insiemi di dati non strutturati estratti da immagini mediche, tenendo conto dei vincoli della OR . Vista l'impossibilità di lavorare con dati medici di tipo DICOM, verrà impiegato un metodo per registrare dataset composti da insiemi di punti non strutturati.
Gli algoritmi proposti sono progettati per trovare la corrispondenza spaziale in forma chiusa tenendo conto del tipo di dati, il vincolo del tempo e la presenza di rumore e /o piccole deformazioni. La teoria e gli algoritmi che abbiamo sviluppato sono derivati dalla teoria delle forme proposta da Kendall (Kendall's shapes) e utilizza un descrittore globale della forma per calcolare le corrispondenze e la distanza tra le strutture coinvolte .
Poiché la registrazione è solo una componente nelle applicazioni mediche, l' ultima parte della tesi è dedicata ad alcune applicazioni pratiche in OR che possono beneficiare della procedura di registrazione .The registration of medical images is necessary to establish spatial correspondences across two or more images.
Registration is rarely the end-goal, but instead, the results of image registration are used in other tasks.
The starting point of this thesis is to analyze which methods at the state of the art of image registration are suitable to be used in assisting a physician during a minimally invasive procedure, such as a percutaneous procedure performed manually or a teleoperated intervention performed by the means of a robot.
The first conclusion is that, even if much previous work has been devoted to develop registration algorithms to be applied in the medical context, most of them are not designed to be used in the operating room scenario (OR) because, compared to other applications, the OR requires also a strong validation, real-time performance and the presence of other instruments.
Almost all of these algorithms are based on a three phase iteration: optimize-transform-evaluate similarity.
In this thesis, we study the feasibility of this three steps approach in the OR, showing the limits that such approach encounter in the applications we are considering. We investigate how could a simple method be realizable and what are the assumptions for such a method to work. We then develop a theory that is suitable to register large sets of unstructured data extracted from medical images keeping into account the constraints of the OR.
The use of the whole radiologic information is not feasible in the OR context, therefore the method we are introducing registers processed dataset extracted from the original medical images.
The framework we propose is designed to find the spatial correspondence in closed form keeping into account the type of the data, the real-time constraint and the presence of noise and/or small deformations. The theory and algorithms we have developed are in the framework of the shape theory proposed by Kendall (Kendall's shapes) and uses a global descriptor of the shape to compute the correspondences and the distance between shapes.
Since the registration is only a component of a medical application, the last part of the thesis is dedicated to some practical applications in the OR that can benefit from the registration procedure
Generalized Shapes and Point Sets Correspondence and Registration
Full text linkThe theory of shapes, as proposed by David Kendall, is concerned with sets of labeled points in the Euclidean space Rd that define a shape regardless of trans- lations, rotations and dilatations. We present here a method that extends the theory of shapes, where, in this case, we use the term generalized shape for structures of unlabeled points. By using the distribution of distances between the points in a set we are able to define the existence of generalized shapes and to infer the computation of the correspondences and the orthogonal transformation between two elements of the same generalized shape equivalence class. This study is oriented to solve the registration of large set of landmarks or point sets derived from medical images but may be employed in other fields such as computer vision or biological morphometry
Multimodal Data Fusion and Registration for Needle Guidance in Percutaneous Procedures
No full textMinimally invasive procedures, such as the percutaneous procedures, present more difficulties than the open approaches due to the limited access to the patient, the limited field of view and the difficult manipulation of the instruments. Navigation systems could help overcome these difficulties by providing additional information to the surgeon or the interventional radiologists during the procedure. In particular they can provide the exact localization of the instruments inside the patients body in relation to the tumor margins and risk structures.
This work presents a method to track, register and integrate pre-operative images, with multimodal data acquired during the actual intervention, in a navigation system for percutaneous procedures. The goal of the navigation system is the virtual reconstruction of the operative scenario by the fusion of different images in the same reference system and the exact localization and tracking of the instruments used during the intervention, such as the ultrasound (US) probe and the needle.
The proposed method focuses on the assistance of percutaneous cryoablation of renal tumors because this procedure requires the surgeon to translate the mental plan developed on the computer tomography (CT) images, acquired before the intervention, into the reality without any hint about internal structures position or only with the assistance of a 2D US image [1].
The success of a percutaneous intervention is bound to the precision of the needle insertion along the planned trajectory.
Together with the registration and fusion of different image datasets, the needle used to accomplish the procedure is calibrated in the same reference system and is represented in the virtual environment. The use of virtual reconstruction increases the awareness of the on going procedure, by providing a rendering of the different tools and structures involved in the intervention and improves the positioning of the needle to be inserted
Trajectory planning with task constraints in densely filled environments
Full text linkIn this paper the problem of computing a rigid object trajectory in an environment populated with deformable objects is addressed. The problem arises in Minimally Invasive Robotic Surgery (MIRS) from the needs of reaching a point of interest inside the anatomy with rigid laparoscopic instruments. We address the case of abdominal surgery. The abdomen is a densely populated soft environment and it is not possible to apply classical techniques for obstacle avoidance because a collision free solution is, most of the time, not feasible. In order to have a convergent algorithm with, at least, one possible solution we have to relax the constraints and allow collision under a specific contact threshold to avoid tissue damaging. In this work a new approach for trajectory planning under these peculiar conditions is implemented. The method computes offline the path which is then tested in a surgical simulator as part of a pre-operative surgical plan
Sistema e metodo per guidare l’inserimento manuale di un ago nel corpo di un paziente durante una procedura chirurgica percutanea
No full textLa presente invenzione è relativa ad un sistema per guidare l’inserimento manuale di un ago nel corpo di un paziente durante una procedura chirurgica percutanea e ad un corrispondente metodo di guida dell’inserimento manuale dell’ago.
In particolare, la presente invenzione trova vantaggiosa, ma non esclusiva applicazione nelle procedure chirurgiche percutanee che fanno uso di aghi per biopsie, cui la descrizione che segue farà esplicito riferimento senza per questo perdere in generalità.
Le procedure diagnostiche e terapeutiche moderne tendono a fare un uso sempre maggiore della biopsia percutanea, che consiste nell’inserire un strumento chirurgico oblungo, tipicamente un ago, nel corpo del paziente sottoposto a diagnosi in modo che la punta dello strumento raggiunga un punto obiettivo all’interno del corpo per prelevare un campione di tessuto biologico (diagnosi) o per trattare una porzione di tessuto biologico di un organo interno (terapia).
Queste procedure richiedono grandi abilità da parte del medico che manovra l’ago, in quanto è sicuramente facile posizionare inizialmente la punta dell’ago nel punto d’ingresso sulla pelle del corpo ma è poi difficile manovrare in modo corretto l’ago per raggiungere il punto obiettivo senza poter vedere l’interno del corpo. E’ noto l’uso apparecchiature di acquisizione di immagini, ad esempio apparecchiature per tomografia computerizzata, risonanza magnetica o ecografie, per acquisire immagini dell’interno del corpo attorno al punto obiettivo allo scopo di verificare il corretto inserimento dell’ago
Marker based accuracy analysis of RGB-D sensor for image guided applications
No full textModern surgical practice is evolving towards less
invasive procedures, where surgeons no longer have a
direct view of the anatomical structures, and therefore
a mental compensation process is required to reach
and identify the desired anatomical area. Image Guide
(IG) procedures have been developed that
automatically integrate information coming from
dierent sensor sources through a registration
procedure. Patient tracking is used to measure the
position and the movements of the patients during
surgery and then to update the relative organ
positions in real-time.
The availability of Microsoft’s Kinect allows addressing
some of the registration problems with a very compact
and inexpensive device. However, it was shown that
Kinect accuracy is only in the centimeters range, and
that it decreases exponentially with distance, making
this sensor unsuitable for use in most IG applications.
In this paper we present our work aimed at increasing
the Kinect performance by introducing simple markers
that can signicantly improve Kinect accuracy and
precision making it compatible with the requirement
of the operating room (OR) tracking
Autonomous Robotic System for Breast Biopsy With Deformation Compensation
Full text linkImage-guided biopsy is the most common technique for breast cancer diagnosis. Although magnetic resonance imaging (MRI) has the highest sensitivity in breast lesion detection, ultrasound (US) biopsy guidance is generally preferred due to its non-invasiveness and real-time image feedback during the insertion. In this work, we propose an autonomous robotic system for US-guided biopsy of breast lesions identified on pre-operative MRI. After initial MRI to breast registration, the US probe attached to the robotic manipulator compresses the breast tissues until a pre-determined force level is reached. This technique, known as preloading, will allow to minimize lesion displacement during the needle insertion. Our workflow integrates a deformation compensation strategy based on patient-specific biomechanical model to update the US probe orientation keeping the target lesion on the US image plane during compression. By relying on a deformation model, the proposed system does not require lesion visibility on US. Experimental evaluation is performed to assess the performance of the system on a realistic breast phantom with 15 internal lesions, considering different preloading forces. The deformation compensation strategy allows to improve localization accuracy, and as a consequence final probe positioning, for all considered lesions. Median lesion localization error is 3.3 mm, which is lower than the median lesion radius, when applying a preloading of 2 N, which guarantees both minimal needle insertion error and tissue stress
A Geometric Approach to Improve Performance of a Collision Detection Algorithm Derived from GJK and LC Algorithms
No full textWe present a fast algorithm for collision detection and for distance computation between two convex objects in 3D. The algorithm is an optimization of Gilbert, Johnson and Keerthi algorithm (GJK) and uses a geometrical approach through the Voronoi regions to detect the closest features, as described in Lin and Canny algorithm (LC). The main contributions of this work are the simplification of each iteration of the GJK algorithm by substituting the computation of the closest point with the identification of the closest feature to the origin and a clear geometric representation and implementation of every iteration. By using the Voronoi regions, together with the above simplification of the calculus, we increase the robustness of the algorithm and we give a deeper understanding of the inner steps.The paper presents a complete description of the proposed procedure showing the approach quality
A Survey on Optical Coherence Tomography—Technology and Application
Full text linkThis paper reviews the main research on Optical Coherence Tomography (OCT), focusing on the progress and advancements made by researchers over the past three decades in its methods and medical imaging applications. By analyzing existing studies and developments, this review aims to provide a foundation for future research in the field
Force control of lightweight series elastic systems using enhanced disturbance observers
Full text linkThis paper analyzes the control challenges associated to lightweight series elastic systems in force control applications, showing that a low end-point inertia can lead to high sensitivity to environment uncertainties. Where mainstream force control methods fail, this paper proposes a control methodology to enhance the performance robustness of existing disturbance observers (DOBs). The approach is validated experimentally and successfully compared to basic control solutions and state of the art DOB approaches
- …
