RGBD Xray imaging system
First design and experimental validation of a mirror-based RGBD Xray imaging system.
fullsize version |
|25 June 2018, MI 03.13.010|
Invited Talk by Prof. Leo Joskowicz
Repeat CT scanning consists of acquiring multiple CT scans of the same patient at various times. It is frequently used in many clinical situations, e.g., to assess disease progression, to evaluate response to treatment and to track the patient and the needle during interventional procedures. The main image analysis goal, which is to identify the changes between the baseline and the follow up scans, is time-consuming, error prone, and requires radiological expertise. Moreover, since each scan adds cumulative radiation that may be harmful to the patient, it is highly desirable to optimize the radiation dose of each scan. However, lower doses reduce image quality and thereby difficult even more the image interpretation task. We have developed a new computational paradigm for on-line radiation dose optimization and automatic change detection in repeat CT scanning. The key principle of our approach is to perform sparse repeat scanning to significantly reduce the radiation dose and to obtain the missing information from the baseline scan without image quality loss. Our approach is unique in that it formulates the problem as sparse sinogram comparison problem in 3D Radon space instead of an image reconstruction problem in image space. We will describe novel methods for registration of the baseline and the repeat scan, for the automatic identification of regions where the changes have occurred, and for image-less needle tracking in interventional radiology. Our experimental results show that these tasks can be accomplished with a dose reduction of about x10.
|27 April 2018, |
CAMP@TUM offers 4 International Undergraduate Excellence Awards in 2018: to the best international undergraduate applicants
The Chair for Computer Aided Medical Procedures (CAMP) would like to offer 4 research awards to strongly motivated international undergraduate students interested in improving their research skills in machine learning, medical imaging, computer vision and/or augmented reality. The students are required to pursue their undergraduate studies outside Germany. The first two awards amount to 4500 Euros and the second two awards to 4000 Euros. These awards will provide financial support for the awardees during their research stay at CAMP for a period of up to three months between June 2018 and October 2019.