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BACKGROUND In recent years, magnetic resonance imaging (MRI) has become important in brain tumor diagnosis. Using this modality, physicians can locate specific pathologies by analyzing differences in tissue character presented in different types of MR images.This paper uses an algorithm integrating fuzzy-c-mean (FCM) and region growing techniques for(More)
We propose and evaluate a systematic approach to detect and classify Patient/Problem, Intervention, Comparison and Outcome (PICO) from the medical literature. The training and test corpora were generated systematically and automatically from structured PubMed abstracts. 23,472 sentences by exact pattern match of head words of P-I-O categories. Afterward,(More)
This paper presents a novel approach to document clustering based on some geometric structure in Combinatorial Topology. Given a set of documents, the set of associations among frequently co-occurring terms in documents forms naturally a simplicial complex. Our general thesis is each connected component of this simplicial complex represents a concept in the(More)
Midline shift (MLS) is one of the most important quantitative features clinicians use to evaluate the severity of brain compression. It can be recognized by modeling brain deformation according to the estimated biomechanical properties of the brain structures. This paper proposes a novel method to identify the deformed midline by decomposing it into three(More)
OBJECTIVES Midline shift (MLS) is an important quantitative feature for evaluating severity of brain compression by various pathologies, including traumatic intracranial hematomas. In this study, we sought to determine the accuracy and the prognostic value of our computer algorithm that automatically measures the MLS of the brain on computed tomography (CT)(More)
Midline shift is one of the most important quantitative features clinicians use to evaluate the severity of brain compression by various pathologies. It can be recognized by modeling brain deformation according to the estimated biomechanical properties of the brain and the cerebrospinal fluid spaces. This paper proposes a novel method to identify the(More)
We propose a multiresolution binary level set method for image segmentation. The binary level set formulation is based on the Song-Chan algorithm, which cannot compute the edge length when the margin of the image is irregular. We modify the edge length approximation so that it can work everywhere in a single-connected image, make it suitable to segment(More)
Midline shift (MLS) is an important quantitative feature clinicians use to evaluate the severity of brain compression by various pathologies. The midline consists of many anatomical structures including the septum pellucidum (SP), a thin membrane between the frontal horns (FH) of the lateral ventricles. We proposed a procedure that can measure MLS by(More)
Overly generalized predictions are a serious problem in concept classiÿcation. In particular, the boundaries among classes are not always clearly deÿned. For example, there are usually uncertainties in diagnoses based on data from biochemical laboratory examinations. Such uncertainties make the prediction be more diicult than noise-free data. To avoid such(More)