Dr. rer. nat. (Computer Science)
Computerized medical systems play a vital role in the operating room, yet surgeons often face challenges when interacting with these systems during surgery. In this project we are aiming at analyzing and understanding the Operating Room specific aspects which affect the end user experience. Beside operating room specific usability evaluation approaches in this project we also try to improve the preliminary intra-operative user interaction methodologies.
Heart attack and stroke are the major causes of human death and atherosclerotic plaques are the most common effect of cardiovascular disease. Intravascular ultrasound (IVUS), a diagnostic imaging technique, offers a unique view of the morphology of the arterial plaque and displays the morphological and histological properties of a cross-section of the vessel. Limitations of the grayscale IVUS manual plaque assessment have led to the development of quantitative techniques for analysis of characteristics of plaque components. In vivo plaque characterization with the so called Virtual Histology (VH)-IVUS, which is based on the ultrasound RF signal processing, is widely available for atherosclerosis plaque characterization in IVUS images. However, it suffers from a poor longitudinal resolution due to the ECG-gated acquisition. The focus of this PhD work is to provide effective methods for image-based vessel plaque characterization via IVUS image analysis to overcome the limitations of current techniques. The proposed algorithms are also applicable to the large amount of the IVUS image sequences obtained from patients in the past, where there is no access to the corresponding radio frequency(RF) data. Since the proposed method is applicable to all IVUS frames of the heart cycle, therefore it outperforms the longitudinal resolution of the so called VH method.
Stroke is the third leading cause of death in Germany. It is a neurology injury, whereby the oxygen supply to parts of the brain gets cut off. About 80% of these strokes are due to ischemia, i.e. an occlusion of a blood vessel leading to an interrupted blood flow. Stenosis inside the carotid artery imaged using four different MR weightings Special setting in this project is the arteria carotis. Plaque is most likely to develop at the branching of the arteria carotis communis into the arteria carotis interna (leading to the brain) and the arteria carotis externa. This can lead to an abnormal narrowing, called a stenosis. According to the American Heart Association these plaques can be divided into different types, based on their consistency and structure. Until now the decision about a surgery was only based on the degree of the stenosis and not on the type of plaque causing it. This is a faulty approach since there is a plaque type (Type IV) which constitutes a relevant clinical danger, although it does not necessary come along with a stenosis. Unlike most other image modalities MR images do not only give information about the degree of the stenosis, but also about the consistency of the plaque. Using different weighted MR images it is possible to correctly classify plaque into the types defined by the AHA. The main goal of this project is to create a classification tool based on T1, T2, Proton Density and 'Time of flight' weighted images. To achieve this goal the arteria carotis and the plaque have to be segmented from the images. Furthermore various features of the plaque have to be extracted in order to get information needed for the classification.
Endovascular stenting is a minimally invasive treatment technique for aortic aneurysms or dissections. Thereby, a certain aortic prosthesis (stent graft) is placed inside the aortic aneurysm in order to prevent a life-threatening rupture of the aortic wall. Prior to the intervention, a computed tomography angiography (CTA) is acquired on which the surgical staff can measure the parameter of the desired stent graft and finalize the intervention workflow. The entire interventional catheter navigation is done under 2D angiography imaging where the physician is missing the important 3D information. The purpose of our project is two-fold:
1. In the planning phase, a modified graph cuts algorithm automatically segments the aorta and aneurysm, so the surgical staff can choose an appropriate type of stent to match the segmented location, length, and diameter of the aneurysm and aorta. By visualizing the defined stent graft next to the three-dimensionally reconstructed aneurysm, mismeasurements can be detected in an early stage. Our main goal is the creation of an interactive simulation system that predicts the behaviour of the aortic wall and the movement of the implanted stent graft.
2. During implantation of the stent graft, after an intensity based registration of CTA and angiography data, the current navigation can be visualized in the 3D CT data set at any time. This includes solutions for electro-magnetic tracking of catheters as well as guide wires and stent grafts. Eventually, Our main goal is the creation of solutions that enable the surgeon to enhance the accuracy of the navigation and positioning, along with a minimum use of angiography, leading to less radiation exposure and less contrast agent injection.
In minimally invasive tumor resection, the goal is to perform a minimal but complete removal of cancerous cells. In the last decades interventional beta probes supported the detection of remaining tumor cells. However, scanning the patient with an intraoperative probe and applying the treatment are not done simultaneously. The main contribution of this work is to extend the one dimensional signal of a nuclear probe to a four dimensional signal including the spatial information of the distal end of the probe. This signal can be then used to guide the surgeon in the resection of residual tissue and thus increase its spatial accuracy while allowing minimal impact on the patient.
In the following lectures I participate as a lecturer:
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| UsersForm |
| Title: || Dr. |
| Firstname: || Ali |
| Middlename: || |
| Lastname: || Bigdelou |
| Picture: || |
| Birthday: || |
| Nationality: || Iran |
| Languages: || English, German, Persian |
| Groups: || Surgical Workflow, Computer-Aided Surgery, Computer Vision, Medical Augmented Reality, 3D Information Presentation, 3D Interaction, HCI in Cars, System Architectures for Ubiquitous Augmented Reality, Machine Learning for Medical Applications |
| Expertise: || Surgical Workflow, Computer-Aided Surgery, 3D Interaction, HCI in Cars, System Architectures for Ubiquitous Augmented Reality |
| Position: || Scientific Staff |
| Status: || Alumni |
| Emailbefore: || ali.bigdelou |
| Emailafter: || cs.tum.edu |
| Room: || IFL |
| Telephone: || |
| Alumniactivity: || Development Specialist and Software Architect at BMW Group, Forschungs- und Innovationszentrum. |
| Defensedate: || 20 November 2012 |
| Thesistitle: || Operating Room Specific Domain Model for Usability Evaluations and HCI Design |
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