We present a bottom-up approach for automatic cancer cell detection in multispectral microscopic thin Pap smear images. Around 4,000 multispectral texture features are explored fo...
We investigate a new, fast and provably convergentMAP reconstruction algorithm for emission tomography. The new algorithm, termed C-OSEM has its origin in the alternating algorith...
3D Electron Microscopy aims at the reconstruction of density volumes corresponding to the mass distribution of macromolecules imaged with an electron microscope. There are many fa...
We propose a new global registration method for estimating the cardiac displacement field in 2D sequences of ultrasound images of the heart. The basic idea is to select a referenc...
In this paper we summarize our results for two classes of hierarchical multi-scale models that exploit contextual information for detection of structure in mammographic imagery. T...
Biomedical imaging of large patient populations, both cross-sectionally and longitudinally, is becoming a standard technique for noninvasive, in-vivo studies of the pathophysiolog...
This paper presents a statistical shape model for automatic skull stripping of MR brain images. A surface model of the brain boundary is hierarchically represented by a set of ove...
This paper focuses on the discussion of using thermal infrared imaging (TIR) in early detection of breast cancer. We use the term thermal texture maps to represent the images captu...
We show the feasibility and the potential of a new signal processing algorithm for the high-resolution deconvolution of OCT signals. Our technique relies on the description of the...