Learn More
This paper presents a novel approach for multi-target tracking using an ensemble framework that optimally chooses target tracking results from that of independent trackers and a detector at each time step. The ensemble model is designed to select the best candidate scored by a function integrating detection confidence, appearance affinity, and smoothness(More)
Segmentation of cells/nuclei is a challenging problem in 2-D histological and cytological images. Although a large number of algorithms have been proposed, newer efforts continue to be devoted to investigate robust models that could have high level of adaptability with regard to considerable amount of image variability. In this paper, we propose a(More)
Cell segmentation is a challenging problem in histology and cytology that can benefit from additional information obtained in using multispectral imaging. Unique transmission spectra of biological tissues are potentially useful for better classification and segmentation of sub-cellular structures. In this paper, we propose a conditional random field (CRF)(More)
BACKGROUND AND PURPOSE Mild hypothermia has been proved to reduce global and focal cerebral ischemic injury in rodents by preventing cellular apoptosis through several pathways. However, whether hypothermia will be beneficial for intracerebral hemorrhage (ICH) and its underlying mechanisms haven't reached a consensus. It has been implicated that endoplasmic(More)
Segmentation of cytological smears plays a critical role in the automated analysis of histological abnormalities by fine needle aspiration cytology. However, smears obtained from fine needle aspiration biopsy are often contaminated with blood. Segmentation of such an image is not a trivial task and the false positive rate could be high if the blood cells(More)
In this paper, we demonstrate the effectiveness of using statistical shape priors to recover shape descriptors from occluded objects in a level set based variational framework. Parameters that balance curve evolution forces are estimated systematically through embedded discrete Conditional Random Field (CRF). In addition, our approach exploits the benefit(More)
Traditional methods for segmenting touching or overlapping objects may lead to the loss of accurate shape information which is a key descriptor in many image analysis applications. While experimental results have shown the effectiveness of using statistical shape priors to overcome such difficulties in a level set based variational framework, problems in(More)
This paper discusses the needs for automated tools to aid in the diagnosis of thyroid nodules based on analysis of fine needle aspiration cytology smears. While conventional practices rely on the analysis of grey scale or RGB color images, we present a multispectral microscopy system that uses thirty-one spectral bands for analysis. Discussed are methods(More)