This paper concerns a method to automatically detect drusen in a retinal image without human supervision or interaction. We use a multi-level approach, beginning with classificatio...
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...
3D object detection and importance regression/ranking are at the core for semantically interpreting 3D medical images of computer aided diagnosis (CAD). In this paper, we propose ...
Le Lu, Jinbo Bi, Matthias Wolf, Marcos Salganicoff
This study develops a procedure for automatic extraction and segmentation of a class-specific object (or region) by learning class-specific boundaries. We present and evaluate t...
Privacy is of growing concern in today's day and age. Protecting the privacy of health data is of paramount importance. With the rapid advancement in imaging technology, anal...