Search results for "Pattern recognition"
showing 10 items of 2301 documents
Multivariate denoising methods combining wavelets and principal component analysis for mass spectrometry data
2010
The identification of new diagnostic or prognostic biomarkers is one of the main aims of clinical cancer research. In recent years, there has been a growing interest in using mass spectrometry for the detection of such biomarkers. The MS signal resulting from MALDI-TOF measurements is contaminated by different sources of technical variations that can be removed by a prior pre-processing step. In particular, denoising makes it possible to remove the random noise contained in the signal. Wavelet methodology associated with thresholding is usually used for this purpose. In this study, we adapted two multivariate denoising methods that combine wavelets and PCA to MS data. The objective was to o…
Probabilistic classification of intracranial gliomas in digital microscope images based on EGFR quantity
2009
A glioma is a type of cancer occurring, in the majority of cases, in the brain. The World Health Organization (WHO) assigns a grade from I to IV to this tumor, with I being the least aggressive and IV being the most aggressive. In glioma cells of grade IV the Epidermal Growth Factor Receptors (EGFRs) are over expressed. In this paper we hypothesize that this overexpression occurs also for gliomas of grades I to III. Moreover, we present a medical study aiming to determine the correlation between the WHO classification and the EGFR quantity in glioma tissue. We define five quantity classes for EGFR. First, results of immunohistochemical staining on brain glioma slices, which visualize the EG…
Hyperspectral image classification using CNN: Application to industrial food packaging
2021
Abstract During food tray packaging, some contamination may exist due to the presence of undesired objects. It is essential to detect anomalies during the packaging process in order to discard the faulty tray and avoid human consumption. This study demonstrates the on-line classification feasibility when using hyperspectral imaging systems for real-time food packaging control by using Convolutional Neural Networks (CNN) as a classifier in heat-sealed food trays. A hyperspectral camera is used to capture individual food tray information and fed to a CNN classifier to detect faulty food trays with object contamination. The proposed system is able to detect up to eleven different contamination…
A Non-linear Diffeomorphic Framework for Prostate Multimodal Registration
2011
International audience; This paper presents a novel method for non-rigid registration of prostate multimodal images based on a nonlinear framework. The parametric estimation of the non-linear diffeomorphism between the 2D fixed and moving images has its basis in solving a set of non-linear equations of thin-plate splines. The regularized bending energy of the thin-plate splines along with the localization error of established correspondences is jointly minimized with the fixed and transformed image difference; where, the transformed image is represented by the set of non-linear equations defined over the moving image. The traditional thin-plate splines with established correspondences may p…
Texture Guided Active Appearance Model Propagation for Prostate Segmentation
2010
Fusion of Magnetic Resonance Imaging (MRI) and Trans Rectal Ultra Sound (TRUS) images during TRUS guided prostate biopsy improves localization of the malignant tissues. Segmented prostate in TRUS and MRI improve registration accuracy and reduce computational cost of the procedure. However, accurate segmentation of the prostate in TRUS images can be a challenging task due to low signal to noise ratio, heterogeneous intensity distribution inside the prostate, and imaging artifacts like speckle noise and shadow. We propose to use texture features from approximation coefficients of Haar wavelet transform for propagation of a shape and appearance based statistical model to segment the prostate i…
Computer-Aided Diagnosis for Prostate Cancer using Multi-Parametric Magnetic Resonance Imaging
2016
Prostate cancer (CaP) is the second most diagnosed cancer in men all over the world.CaP growth is characterized by two main types of evolution: (i) the slow-growing tumours progress slowly and usually remain confined to the prostate gland; (ii) the fast-growing tumours metastasize from prostate gland to other organs, which might lead to incurable diseases.Therefore, early diagnosis and risk assessment play major roles in patient treatment and follow-up.In the last decades, new imaging techniques based on Magnetic Resonance Imaging (MRI) have been developed improving diagnosis.In practise, diagnosis can be affected by multiple factors such as observer variability and visibility and complexit…
A computer system to perform structure comparison using TOPS representations of protein structure
2001
We describe the design and implementation of a fast topology-based method for protein structure comparison. The approach uses the TOPS topological representation of protein structure, aligning two structures using a common discovered pattern and generating measure of distance derived from an insert score. Heavy use is made of a constraint-based pattern-matching algorithm for TOPS diagrams that we have designed and described elsewhere (Bioinformatics 15(4) (1999) 317). The comparison system is maintained at the European Bioinformatics Institute and is available over the Web at tops.ebi.ac.uk/tops. Users submit a structure description in Protein Data Bank (PDB) format and can compare it with …
Assessing the low complexity of protein sequences via the low complexity triangle.
2020
Background Proteins with low complexity regions (LCRs) have atypical sequence and structural features. Their amino acid composition varies from the expected, determined proteome-wise, and they do not follow the rules of structural folding that prevail in globular regions. One way to characterize these regions is by assessing the repeatability of a sequence, that is, calculating the local propensity of a region to be part of a repeat. Results We combine two local measures of low complexity, repeatability (using the RES algorithm) and fraction of the most frequent amino acid, to evaluate different proteomes, datasets of protein regions with specific features, and individual cases of proteins…
Judging the contact-times of multiple objects: Evidence for asymmetric interference.
2009
The accuracy of time-to-contact (TTC) judgments for single approaching objects is well researched, however, close to nothing is known about our ability to make simultaneous TTC judgments for two or more objects. Such complex judgments are required in many everyday situations, for instance when crossing a multi-lane street or when engaged in multi-player ball games. We used a prediction-motion paradigm in which participants simultaneously estimated the absolute TTC of two objects, and compared the performance to a standard single-object condition. Results showed that the order of arrival of the two objects determined the accuracy of the TTC estimates: Estimation of the first-arriving object …
Integration of local features into a global shape
2001
AbstractIt is a well-established fact that the cortical filters selective for spatial frequency and orientation have a limited spatial extent. The present study investigated how information from local filters is integrated into global shapes. Specifically, we were interested in whether identification of a global pattern consisting of small oriented, spatially-bandpass features (Gabor patches) depends on the orientations of those features. The observer was presented with a C-like stimulus shape comprised of oriented Gabor elements on a blank background, and the performance measure was the threshold contrast for identifying the global orientation of the C-shape (four possible rotated orientat…