Domain Adaptation in remote sensing: increasing the portability of land-cover classifiers

Among the types of remote sensing acquisitions, optical images are certainly one of the most widely relied upon data sources for Earth observation. They provide detailed measurements of the electromagnetic radiation reflected or emitted by each pixel in the scene. Through a process termed supervised land-cover classification, this allows to automatically yet accurately distinguish objects at the surface of our planet. In this respect, when producing a land-cover map of the surveyed area, the availability of training examples representative of each thematic class is crucial for the success of the classification procedure. However, in real applications, due to several constraints on the sample collection process, labeled pixels are usually scarce. When analyzing an image for which those key samples are unavailable, a viable solution consists in resorting to the ground truth data of other previously acquired images. This option is attractive but several factors such as atmospheric, ground and acquisition conditions can cause radiometric differences between the images, hindering therefore the transfer of knowledge from one image to another. The goal of this Thesis is to supply remote sensing image analysts with suitable processing techniques to ensure a robust portability of the classification models across different images. The ultimate purpose is to map the land-cover classes over large spatial and temporal extents with minimal ground information. To overcome, or simply quantify, the observed shifts in the statistical distribution of the spectra of the materials, we study four approaches issued from the field of machine learning. First, we propose a strategy to intelligently sample the image of interest to collect the labels only in correspondence of the most useful pixels. This iterative routine is based on a constant evaluation of the pertinence to the new image of the initial training data actually belonging to a different image. Second, an approach to reduce the radiometric differences among the images by projecting the respective pixels in a common new data space is presented. We analyze a kernel-based feature extraction framework suited for such problems, showing that, after this relative normalization, the cross-image generalization abilities of a classifier are highly increased. Third, we test a new data-driven measure of distance between probability distributions to assess the distortions caused by differences in the acquisition geometry affecting series of multi-angle images. Also, we gauge the portability of classification models through the sequences. In both exercises, the efficacy of classic physically- and statistically-based normalization methods is discussed. Finally, we explore a new family of approaches based on sparse representations of the samples to reciprocally convert the data space of two images. The projection function bridging the images allows a synthesis of new pixels with more similar characteristics ultimately facilitating the land-cover mapping across images.

La stratégie thérapeutique anti-VEGF améliore le pronostic visuel de la dégénérescence maculaire liée à l'âge exsudative [Intravitreal anti-VEGF injections improve the visual prognosis of wet age related macular degeneration].

Age related macular degeneration (AMD) is an ocular disease with high prevalence among elderly persons. Two different forms exist: dry AMD, usually slowly progressive, and neovascular AMD (wet form) more aggressive. Photodynamic therapy is used to treat the wet form and anti VEGF treatments recently became available and offer a real change in the prognostic of wet AMD. Two products are registered and used in Switzerland (Macugen and Lucentis), a third "off labels product", Avastin is also currently used in clinical practice. Nevertheless, both the duration of treatment and the number of injection requested to stabilise the disease were not defined in the studies. Ongoing studies are mainly evaluating combined treatments and long acting form of the drug.

CD3 delta establishes a functional link between the T cell receptor and CD8.

T cells expressing T cell receptor (TCR) complexes that lack CD3 delta, either due to deletion of the CD3 delta gene, or by replacement of the connecting peptide of the TCR alpha chain, exhibit severely impaired positive selection and TCR-mediated activation of CD8 single-positive T cells. Because the same defects have been observed in mice expressing no CD8 beta or tailless CD8 beta, we examined whether CD3 delta serves to couple TCR.CD3 with CD8. To this end we used T cell hybridomas and transgenic mice expressing the T1 TCR, which recognizes a photoreactive derivative of the PbCS 252-260 peptide in the context of H-2K(d). We report that, in thymocytes and hybridomas expressing the T1 TCR.CD3 complex, CD8 alpha beta associates with the TCR. This association was not observed on T1 hybridomas expressing only CD8 alpha alpha or a CD3 delta(-) variant of the T1 TCR. CD3 delta was selectively co-immunoprecipitated with anti-CD8 antibodies, indicating an avid association of CD8 with CD3 delta. Because CD8 alpha beta is a raft constituent, due to this association a fraction of TCR.CD3 is raft-associated. Cross-linking of these TCR-CD8 adducts results in extensive TCR aggregate formation and intracellular calcium mobilization. Thus, CD3 delta couples TCR.CD3 with raft-associated CD8, which is required for effective activation and positive selection of CD8(+) T cells.

Navigator-gated free-breathing 3D balanced FFE projection renal MRA: Comparison with contrast-enhanced breath-hold 3D MRA in a swine model.

A cardiac-triggered, free-breathing, 3D balanced FFE projection renal MR angiography (MRA) technique with a 2D pencil beam aortic labeling pulse for selective aortic spin tagging was developed. For respiratory motion artifact suppression during free breathing, a prospective real-time navigator was implemented for renal MRA. Images obtained with the new approach were compared with standard contrast-enhanced (CE) 3D breath-hold MRA in seven swine. Signal properties and vessel visualization were analyzed. With the presented technique, high-resolution, high-contrast renal projection MRA with superior vessel length visualization (including a greater visible number of distal branches of the renal arteries) compared to standard breath-hold CE-MRA was obtained. The present results warrant clinical studies in patients with renal artery disease.

Large-scale clustering through functional embedding

We present a new framework for large-scale data clustering. The main idea is to modify functional dimensionality reduction techniques to directly optimize over discrete labels using stochastic gradient descent. Compared to methods like spectral clustering our approach solves a single optimization problem, rather than an ad-hoc two-stage optimization approach, does not require a matrix inversion, can easily encode prior knowledge in the set of implementable functions, and does not have an ?out-of-sample? problem. Experimental results on both artificial and real-world datasets show the usefulness of our approach.

Proton NMR of (15)N-choline metabolites enhanced by dynamic nuclear polarization.

Chemical shifts of protons can report on metabolic transformations such as the conversion of choline to phosphocholine. To follow such processes in vivo, magnetization can be enhanced by dynamic nuclear polarization (DNP). We have hyperpolarized in this manner nitrogen-15 spins in (15)N-labeled choline up to 3.3% by irradiating the 94 GHz electron spin resonance of admixed TEMPO nitroxide radicals in a magnetic field of 3.35 T during ca. 3 h at 1.2 K. The sample was subsequently transferred to a high-resolution magnet, and the enhanced polarization was converted from (15)N to methyl- and methylene protons, using the small (2,3)J((1)H,(15)N) couplings in choline. The room-temperature lifetime of nitrogen polarization in choline, T(1)((15)N) approximately 200 s, could be considerably increased by partial deuteration of the molecule. This procedure enables studies of choline metabolites in vitro and in vivo using DNP-enhanced proton NMR.

A pipeline approach with spatial information for segmenting multiple sclerosis lesions on brain magnetic resonance imaging

Background: Conventional magnetic resonance imaging (MRI) techniques are highly sensitive to detect multiple sclerosis (MS) plaques, enabling a quantitative assessment of inflammatory activity and lesion load. In quantitative analyses of focal lesions, manual or semi-automated segmentations have been widely used to compute the total number of lesions and the total lesion volume. These techniques, however, are both challenging and time-consuming, being also prone to intra-observer and inter-observer variability.Aim: To develop an automated approach to segment brain tissues and MS lesions from brain MRI images. The goal is to reduce the user interaction and to provide an objective tool that eliminates the inter- and intra-observer variability.Methods: Based on the recent methods developed by Souplet et al. and de Boer et al., we propose a novel pipeline which includes the following steps: bias correction, skull stripping, atlas registration, tissue classification, and lesion segmentation. After the initial pre-processing steps, a MRI scan is automatically segmented into 4 classes: white matter (WM), grey matter (GM), cerebrospinal fluid (CSF) and partial volume. An expectation maximisation method which fits a multivariate Gaussian mixture model to T1-w, T2-w and PD-w images is used for this purpose. Based on the obtained tissue masks and using the estimated GM mean and variance, we apply an intensity threshold to the FLAIR image, which provides the lesion segmentation. With the aim of improving this initial result, spatial information coming from the neighbouring tissue labels is used to refine the final lesion segmentation.Results:The experimental evaluation was performed using real data sets of 1.5T and the corresponding ground truth annotations provided by expert radiologists. The following values were obtained: 64% of true positive (TP) fraction, 80% of false positive (FP) fraction, and an average surface distance of 7.89 mm. The results of our approach were quantitatively compared to our implementations of the works of Souplet et al. and de Boer et al., obtaining higher TP and lower FP values.Conclusion: Promising MS lesion segmentation results have been obtained in terms of TP. However, the high number of FP which is still a well-known problem of all the automated MS lesion segmentation approaches has to be improved in order to use them for the standard clinical practice. Our future work will focus on tackling this issue.

A review of atlas-based segmentation for magnetic resonance brain images.

Normal and abnormal brains can be segmented by registering the target image with an atlas. Here, an atlas is defined as the combination of an intensity image (template) and its segmented image (the atlas labels). After registering the atlas template and the target image, the atlas labels are propagated to the target image. We define this process as atlas-based segmentation. In recent years, researchers have investigated registration algorithms to match atlases to query subjects and also strategies for atlas construction. In this paper we present a review of the automated approaches for atlas-based segmentation of magnetic resonance brain images. We aim to point out the strengths and weaknesses of atlas-based methods and suggest new research directions. We use two different criteria to present the methods. First, we refer to the algorithms according to their atlas-based strategy: label propagation, multi-atlas methods, and probabilistic techniques. Subsequently, we classify the methods according to their medical target: the brain and its internal structures, tissue segmentation in healthy subjects, tissue segmentation in fetus, neonates and elderly subjects, and segmentation of damaged brains. A quantitative comparison of the results reported in the literature is also presented.

The QUASAR reproducibility study, Part II: Results from a multi-center Arterial Spin Labeling test-retest study.

Arterial Spin Labeling (ASL) is a method to measure perfusion using magnetically labeled blood water as an endogenous tracer. Being fully non-invasive, this technique is attractive for longitudinal studies of cerebral blood flow in healthy and diseased individuals, or as a surrogate marker of metabolism. So far, ASL has been restricted mostly to specialist centers due to a generally low SNR of the method and potential issues with user-dependent analysis needed to obtain quantitative measurement of cerebral blood flow (CBF). Here, we evaluated a particular implementation of ASL (called Quantitative STAR labeling of Arterial Regions or QUASAR), a method providing user independent quantification of CBF in a large test-retest study across sites from around the world, dubbed "The QUASAR reproducibility study". Altogether, 28 sites located in Asia, Europe and North America participated and a total of 284 healthy volunteers were scanned. Minimal operator dependence was assured by using an automatic planning tool and its accuracy and potential usefulness in multi-center trials was evaluated as well. Accurate repositioning between sessions was achieved with the automatic planning tool showing mean displacements of 1.87+/-0.95 mm and rotations of 1.56+/-0.66 degrees . Mean gray matter CBF was 47.4+/-7.5 [ml/100 g/min] with a between-subject standard variation SD(b)=5.5 [ml/100 g/min] and a within-subject standard deviation SD(w)=4.7 [ml/100 g/min]. The corresponding repeatability was 13.0 [ml/100 g/min] and was found to be within the range of previous studies.

Influence of label information on dark chocolate acceptability

The aim of the present work was to study how the information on product labels influences consumer expectations and their acceptance and purchase intention of dark chocolate. Six samples of dark choco- late, varying in brand (premium and store brand) and in type of product (regular dark chocolate, single cocoa origin dark chocolate and high percentage of cocoa dark chocolate), were evaluated by 109 con- sumers who scored their liking and purchase intention under three conditions: blind (only tasting the products), expected (observing product label information) and informed (tasting the products together with provision of the label information). In the expected condition, consumer liking was mainly affected by the brand. In the blind condition, differences in liking were due to the type of product; the samples with a high percentage of cocoa were those less preferred by consumers. Under the informed condition, liking of dark chocolates varied depending on both brand and type of product. Premium brand chocolates generated high consumer expectations of chocolate acceptability, which were fulfilled by the sensory characteristics of the products. Store brand chocolates created lower expectations, but when they were tasted they were as acceptable as premium chocolates. Claims of a high percentage of cocoa and single cocoa origin on labels did not generate higher expectations than regular dark chocolates.

Aplicació de verificació i control de codi de barres i datamatrix

A les línies de producció de l’empresa Laboratorios Hipra, s’ha plantejat imprimir els codis de les caixes mitjançant nous làsers amb la tècnica de delineat làser, amb aquests nous models de làser es vol imprimir codis datamatrix. Per tal que això sigui possible, és molt important poder tenir un control de les impressions realitzades pel làser, ja que en cas contrari, podrien empaquetar-se caixes amb un marcatge erroni. S’ha dissenyatuna aplicació capaç de verificar i controlar les impressions realitzades pels làsers. Aquesta aplicació ha de ser capaç de verificar i controlar les caixes marcades tant amb codis de barres com amb datamatrix, a més a més de mostrar totes les dades dels marcatges per una pantalla SCADA. L’aplicació també incorpora un sistema d’expulsió de les caixes amb un marcatge d’inferior qualitat a la desitjada en cada moment

Effects of epitope modification on T cell receptor-ligand binding and antigen recognition by seven H-2Kd-restricted cytotoxic T lymphocyte clones specific for a photoreactive peptide derivative.

We tested for antigen recognition and T cell receptor (TCR)-ligand binding 12 peptide derivative variants on seven H-2Kd-restricted cytotoxic T lymphocytes (CTL) clones specific for a bifunctional photoreactive derivative of the Plasmodium berghei circumsporozoite peptide 252-260 (SYIPSAEKI). The derivative contained iodo-4-azidosalicylic acid in place of PbCS S-252 and 4-azidobenzoic acid on PbCS K-259. Selective photoactivation of the N-terminal photoreactive group allowed crosslinking to Kd molecules and photoactivation of the orthogonal group to TCR. TCR photoaffinity labeling with covalent Kd-peptide derivative complexes allowed direct assessment of TCR-ligand binding on living CTL. In most cases (over 80%) cytotoxicity (chromium release) and TCR-ligand binding differed by less than fivefold. The exceptions included (a) partial TCR agonists (8 cases), for which antigen recognition was five-tenfold less efficient than TCR-ligand binding, (b) TCR antagonists (2 cases), which were not recognized and capable of inhibiting recognition of the wild-type conjugate, (c) heteroclitic agonists (2 cases), for which antigen recognition was more efficient than TCR-ligand binding, and (d) one partial TCR agonist, which activated only Fas (C1)95), but not perforin/granzyme-mediated cytotoxicity. There was no correlation between these divergences and the avidity of TCR-ligand binding, indicating that other factors than binding avidity determine the nature of the CTL response. An unexpected and novel finding was that CD8-dependent clones clearly incline more to TCR antagonism than CD8-independent ones. As there was no correlation between CD8 dependence and the avidity of TCR-ligand binding, the possibility is suggested that CD8 plays a critical role in aberrant CTL function.

Local re-inversion coronary MR angiography: arterial spin-labeling without the need for subtraction.

PURPOSE: To implement a double-inversion bright-blood coronary MR angiography sequence using a cylindrical re-inversion prepulse for selective visualization of the coronary arteries. MATERIALS AND METHODS: Local re-inversion bright-blood magnetization preparation was implemented using a nonselective inversion followed by a cylindrical aortic re-inversion prepulse. After an inversion delay that allows for in-flow of the labeled blood-pool into the coronary arteries, three-dimensional radial steady-state free-precession (SSFP) imaging (repetition/echo time, 7.2/3.6 ms; flip angle, 120 degrees, 16 profiles per RR interval; field of view, 360 mm; matrix, 512, twelve 3-mm slices) is performed. Coronary MR angiography was performed in three healthy volunteers and in one patient on a commercial 1.5 Tesla whole-body MR System. RESULTS: In all subjects, coronary arteries were selectively visualized with positive contrast. In addition, a middle-grade stenosis of the proximal right coronary artery was seen in one patient. CONCLUSION: A novel T1 contrast-enhancement strategy is presented for selective visualization of the coronary arteries without extrinsic contrast medium application. In comparison to former arterial spin-labeling schemes, the proposed magnetization preparation obviates the need for a second data set and subtraction.

T cell recognition of hapten. Anatomy of T cell receptor binding of a H-2kd-associated photoreactive peptide derivative.

To elucidate the structural basis of T cell recognition of hapten-modified antigenic peptides, we studied the interaction of the T1 T cell antigen receptor (TCR) with its ligand, the H-2Kd-bound Plasmodium berghei circumsporozoite peptide 252-260 (SYIPSAEKI) containing photoreactive 4-azidobenzoic acid (ABA) on P. berghei circumsporozoite Lys259. The photoaffinity-labeled TCR residue(s) were mapped as Tyr48 and/or Tyr50 of complementary determining region 2beta (CDR2beta). Other TCR-ligand contacts were identified by mutational analysis. Molecular modeling, based on crystallographic coordinates of closely related TCR and major histocompatibility complex I molecules, indicated that ABA binds strongly and specifically in a cavity between CDR3alpha and CDR2beta. We conclude that TCR expressing selective Vbeta and CDR3alpha sequences form a binding domain between CDR3alpha and CDR2beta that can accommodate nonpeptidic moieties conjugated at the C-terminal portion of peptides binding to major histocompatibility complex (MHC) encoded proteins.

Cluster-based active learning for compact image classification

In this paper, we consider active sampling to label pixels grouped with hierarchical clustering. The objective of the method is to match the data relationships discovered by the clustering algorithm with the user's desired class semantics. The first is represented as a complete tree to be pruned and the second is iteratively provided by the user. The active learning algorithm proposed searches the pruning of the tree that best matches the labels of the sampled points. By choosing the part of the tree to sample from according to current pruning's uncertainty, sampling is focused on most uncertain clusters. This way, large clusters for which the class membership is already fixed are no longer queried and sampling is focused on division of clusters showing mixed labels. The model is tested on a VHR image in a multiclass classification setting. The method clearly outperforms random sampling in a transductive setting, but cannot generalize to unseen data, since it aims at optimizing the classification of a given cluster structure.