MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. The cardiac valvular apparatus, composed of the aortic, mitral, pulmonary and tricuspid valve, is an essential part of the anatomical, functional and hemodynamic characte...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
We propose a framework for the extraction of biomarkers from low-dimensional manifolds representing inter- and intra-subject brain variation in MR image data. The coordinates of ea...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
The high dimensionality of functional magnetic resonance imaging (fMRI) data presents major challenges to fMRI pattern classification. Directly applying standard classifiers often ...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. Heart isolation (separating the heart from the proximity tissues, e.g., lung, liver, and rib cage) is a prerequisite to clearly visualize the coronary arteries in 3D. Suc...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
The use of machine learning tools is gaining popularity in neuroimaging, as it provides a sensitive assessment of the information conveyed by brain images. In particular, finding ...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. This paper presents a method for automatic color and intensity normalization of digitized histology slides stained with two different agents. In comparison to previous a...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
Lymph node detection and measurement is a difficult and important part of cancer treatment. In this paper we present a robust and effective learning-based method for the automatic...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
To regularize cardiac motion recovery from medical images, electromechanical models are increasingly popular for providing a priori physiological motion information. Although these...
MICCAI
2010
Springer
13 years 10 months ago
2010
Springer
Abstract. A new algorithm is presented for the automatic segmentation of Multiple Sclerosis (MS) lesions in 3D MR images. It builds on the discriminative random decision forest fra...