This work concerns with linear and spatially-adaptive direct reconstruction algorithms for 2-D parallel-beam transmission tomography, extending the Filtered Back-Projection (FBP)....
Probabilistic branching node inference is an important step for analyzing branching patterns involved in many anatomic structures. We propose combining machine learning techniques...
Haibin Ling, Michael Barnathan, Vasileios Megalooi...
We address the problem of zero-order-free image reconstruction in digital holographic microscopy. We show how the goal can be achieved by confining the object-wave modulation to ...
Chandra Sekhar Seelamantula, Nicolas Pavillon, Chr...
We present a numerical framework for Fluorescence Diffuse Optical Tomography (fDOT) that combines a forward model together with an iterative reconstruction procedure. Using rapid ...
Biological images have the potential to reveal complex signatures that may not be amenable to morphological modeling in terms of shape, location, texture, and color. An effective ...
Various cortical measures such as cortical thickness are routinely computed along the vertices of cortical surface meshes. These metrics are used in surface-based morphometric stu...
One of the main challenges for Content-Based Image Retrieval (CBIR) is to achieve meaningful mappings between the high-level semantic concepts and the low-level visual features in...
Haiying Guan, Sameer Antani, L. Rodney Long, Georg...
Dynamic cardiac metrics, including myocardial strains and displacements, provide a quantitative approach to evaluate cardiac function. However, in current clinical diagnosis, larg...
In this paper we propose a fast method to detect spiculated lesions and architectural distortions in Digital Breast Tomosynthesis datasets. This approach relies on an a contrario ...
Giovanni Palma, Serge Muller, Isabelle Bloch, Razv...
A novel method for the segmentation of brain structures combining registration-based and EM-based approaches is proposed. To address the issue of intensity variation within brain ...
Maria Murgasova, David Edwards, Joseph V. Hajnal, ...