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We present a framework for identifying disease states by classifying cells in the pathological regions of tissues into different categories. We use conditional random fields (CRF) to incorporate characteristics of cells and their spatial distributions. The efficacy of CRF to model cell-cell feature interactions is demonstrated by using a lung tissue dataset and a synthesized cancer tissue dataset...
This paper proposes a novel approach for segmenting fetal ultrasound images. This problem presents a variety of challenges including high noise, low contrast, and other US imaging properties such as similarity between texture and gray levels of two organs/ tissues. In this paper, we have proposed a Conditional Random Field (CRF) based framework to handle challenges in segmenting fetal ultrasound images...
Skin lesion pigmentation area from surface, or, epi-illumination (ELM) images and blood volume area from transillumination (TLM) images are useful features to aid a dermatologist in the diagnosis of melanoma and other skin cancers in early curable stages. However, segmentation of these areas is difficult. In this work, we present an automatic segmentation tool for ELM and TLM images that also provides...
In this paper, we present an interactive method for liver tumor segmentation from computed tomography (CT) scans. After some pre-processing operations, including liver parenchyma segmentation and liver contrast enhancement, the CT volume is partitioned into a large number of catchment basins under watershed transform. Then a support vector machines (SVM) classifier is trained on the user-selected...
The spermatogenesis is crucial to the species reproduction, and its monitoring may shed light over some important information of such process. Thus, the germ cells quantification can provide useful tools to improve the reproduction cycle. In this paper, we present the first work that address this problem in fishes with machine learning techniques. We show here how to obtain high recognition accuracies...
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