112 research outputs found
Histopathological image analysis : a review
Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe
Structured Random Matrices
Random matrix theory is a well-developed area of probability theory that has
numerous connections with other areas of mathematics and its applications. Much
of the literature in this area is concerned with matrices that possess many
exact or approximate symmetries, such as matrices with i.i.d. entries, for
which precise analytic results and limit theorems are available. Much less well
understood are matrices that are endowed with an arbitrary structure, such as
sparse Wigner matrices or matrices whose entries possess a given variance
pattern. The challenge in investigating such structured random matrices is to
understand how the given structure of the matrix is reflected in its spectral
properties. This chapter reviews a number of recent results, methods, and open
problems in this direction, with a particular emphasis on sharp spectral norm
inequalities for Gaussian random matrices.Comment: 46 pages; to appear in IMA Volume "Discrete Structures: Analysis and
Applications" (Springer
Retrospective suspect and non-target screening combined with similarity measures to prioritize MDMA and amphetamine synthesis markers in wastewater
3,4-Methylenedioxymethamphetamine (MDMA) and amphetamine are commonly used psychoactive stimulants. Illegal manufacture of these substances, mainly located in the Netherlands and Belgium, generates large amounts of chemical waste which is disposed in the environment or released in sewer systems. Retrospective analysis of high-resolution mass spectrometry (HRMS) data was implemented to detect synthesis markers of MDMA and amphetamine production in wastewater samples. Specifically, suspect and non-target screening, combined with a prioritization approach based on similarity measures between detected features and mass loads of MDMA and amphetamine was implemented. Two hundred and thirty-five 24 h-composite wastewater samples collected from a treatment plant in the Netherlands between 2016 and 2018 were analyzed by liquid chromatography coupled to high-resolution mass spectrometry. Samples were initially separated into two groups (i.e., baseline consumption versus dumping) based on daily loads of MDMA and amphetamine. Significance testing and fold-changes were used to find differences between features in the two groups. Then, associations between peak areas of all features and MDMA or amphetamine loads were investigated across the whole time series using various measures (Euclidian distance, Pearson's correlation coefficient, Spearman's rank correlation coefficient, distance correlation and maximum information coefficient). This unsupervised and unbiased approach was used for prioritization of features and allowed the selection of 28 presumed markers of production of MDMA and amphetamine. These markers could potentially be used to detect dumps in sewer systems, help in determining the synthesis route and track down the waste in the environment
Sparsity and Incoherence in Compressive Sampling
We consider the problem of reconstructing a sparse signal from a
limited number of linear measurements. Given randomly selected samples of
, where is an orthonormal matrix, we show that minimization
recovers exactly when the number of measurements exceeds where is the number of
nonzero components in , and is the largest entry in properly
normalized: . The smaller ,
the fewer samples needed.
The result holds for ``most'' sparse signals supported on a fixed (but
arbitrary) set . Given , if the sign of for each nonzero entry on
and the observed values of are drawn at random, the signal is
recovered with overwhelming probability. Moreover, there is a sense in which
this is nearly optimal since any method succeeding with the same probability
would require just about this many samples
Some inequalities on generalized entropies
We give several inequalities on generalized entropies involving Tsallis
entropies, using some inequalities obtained by improvements of Young's
inequality. We also give a generalized Han's inequality.Comment: 15 page
Restricted Isometries for Partial Random Circulant Matrices
In the theory of compressed sensing, restricted isometry analysis has become
a standard tool for studying how efficiently a measurement matrix acquires
information about sparse and compressible signals. Many recovery algorithms are
known to succeed when the restricted isometry constants of the sampling matrix
are small. Many potential applications of compressed sensing involve a
data-acquisition process that proceeds by convolution with a random pulse
followed by (nonrandom) subsampling. At present, the theoretical analysis of
this measurement technique is lacking. This paper demonstrates that the th
order restricted isometry constant is small when the number of samples
satisfies , where is the length of the pulse.
This bound improves on previous estimates, which exhibit quadratic scaling
Estimation in high dimensions: a geometric perspective
This tutorial provides an exposition of a flexible geometric framework for
high dimensional estimation problems with constraints. The tutorial develops
geometric intuition about high dimensional sets, justifies it with some results
of asymptotic convex geometry, and demonstrates connections between geometric
results and estimation problems. The theory is illustrated with applications to
sparse recovery, matrix completion, quantization, linear and logistic
regression and generalized linear models.Comment: 56 pages, 9 figures. Multiple minor change
Paraphrastic Reformulations in Spoken Corpora
International audienceOur work addresses the automatic detection of paraphrastic reformulation in French spoken corpora. The proposed approach is syn-tagmatic. It is based on specific markers and the specificities of the spoken language. Manual multi-dimensional annotation performed by two annotators provides fine-grained reference data. An automatic method is proposed in order to decide whether sentences contain or not paraphras-tic relations. The obtained results show up to 66.4% precision. Analysis of the manual annotations indicates that few paraphrastic segments show morphological modifications (inflection, derivation or compounding) and that the syntactic equivalence between the segments is seldom respected, as these usually belong to different syntactic categories
CD8beta Endows CD8 with Efficient Coreceptor Function by Coupling T Cell Receptor/CD3 to Raft-associated CD8/p56lck Complexes
The extraordinary sensitivity of CD8+ T cells to recognize antigen impinges to a large extent on the coreceptor CD8. While several studies have shown that the CD8beta chain endows CD8 with efficient coreceptor function, the molecular basis for this is enigmatic. Here we report that cell-associated CD8alphabeta, but not CD8alphaalpha or soluble CD8alphabeta, substantially increases the avidity of T cell receptor (TCR)-ligand binding. To elucidate how the cytoplasmic and transmembrane portions of CD8beta endow CD8 with efficient coreceptor function, we examined T1.4 T cell hybridomas transfected with various CD8beta constructs. T1.4 hybridomas recognize a photoreactive Plasmodium berghei circumsporozoite (PbCS) peptide derivative (PbCS (4-azidobezoic acid [ABA])) in the context of H-2K(d), and permit assessment of TCR-ligand binding by TCR photoaffinity labeling. We find that the cytoplasmic portion of CD8beta, mainly due to its palmitoylation, mediates partitioning of CD8 in lipid rafts, where it efficiently associates with p56(lck). In addition, the cytoplasmic portion of CD8beta mediates constitutive association of CD8 with TCR/CD3. The resulting TCR-CD8 adducts exhibit high affinity for major histocompatibility complex (MHC)-peptide. Importantly, because CD8alphabeta partitions in rafts, its interaction with TCR/CD3 promotes raft association of TCR/CD3. Engagement of these TCR/CD3-CD8/lck adducts by multimeric MHC-peptide induces activation of p56(lck) in rafts, which in turn phosphorylates CD3 and initiates T cell activation
Histopathological image analysis: a review,”
Abstract-Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe
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