Segmentation of medical images is commonly formulated as a supervised learning problem, where manually labeled training data are summarized using a parametric atlas. Summarizing th...
Mert R. Sabuncu, B. T. Thomas Yeo, Koen Van Leem...
Challenging object detection and segmentation tasks can be facilitated by the availability of a reference object. However, accounting for possible transformations between the diff...
In recent years Kernel Principal Component Analysis (Kernel PCA) has gained much attention because of its ability to capture nonlinear image features, which are particularly impor...
The effectiveness and clinical benefits of image guided surgery are
well established for procedures where there is manageable tissue motion. In
minimally invasive cardiac, gastro...
Object detection and recognition has achieved a significant progress in recent years. However robust 3D object detection and segmentation in noisy 3D data volumes remains a challen...
Le Lu, Adrian Barbu, Matthias Wolf, Jianming Liang...