Improving Satellite Image Based Forest Inventory by Using A Priori Site Quality Information

Summary

The Cave by José Saramago: Platonic image versus metaphysics

The cave by José Saramago has as a certain reference the image of the cave of book VII of Plato's Republic and, however, Saramago is not an idealistic or metaphysical writer. This article, taking advantage of the applicability with which Plato endowed his image, defends the urge to be open to the messages sent by the earth, by matter, the urge not to become prisoners in the golden caves of the Western society and, finally, the urge to find our freedom in Nature, phýsis, and not far or beyond, metá, it.

The "image" of the cave and the constant temptation to correct Plato: Benjamin Jowettt as an example

Translations of the first chapters of Book VII of Plato's Republic, in which he introduces the well-known image of the cave, eikón, reveals an astonishing and intriguing variety of interpretations of this image: "allegory", "myth", "fable", "parable", "simile" and "comparison", to cite but a few. Taking as an example the work by Benjamin Jowett, the Victorian translator of Plato, remarkable for its textual accuracy and by means of a close analysis of the terms related to the image, this paper insists on the need to neither interpret nor correct the great ideal philosopher, in this case revealing some evident contradictions that arise when this advice is not followed and pointing out the occasional use of terms extraneous to the Platonic lexicon such as "allegory".

Intravitreal ranibizumab for age-related macular degeneration - optical coherence tomography guided retreatment intervals and their intra- and inter-individual variability

PURPOSE:To determine whether the need for retreatment after an initial loading phase of 3 monthly intravitreal injections of ranibizumab shows an intra-individual regular rhythm and to what degree it varies between different patients.SETTING:Prospective mono-centre cohort study.METHODS:Prospective study with 42 patients with exudative age-related macular degeneration (AMD), treatment na?ve, giving informed consent. Loading dose of 3 monthly doses of ranibizumab (0,5mg), followed by a 12 months pro re nata (PRN) regimen according to early exudative signs on spectral domain optical coherence tomography (HD-OCT Cirrus Zeiss?, cube 512x126). The follow-up visits were intensified (week 4, 5, 6, 7, 8, 10, 12, 14, 16, 20, 24, etc after each injection) in order to detect exudative recurrences early, and injection followed within 3 days in cases of subretinal fluid, or intraretinal cysts, or central thickness increase of >50?m. Intervals were calculated between injections and the following recurrence was calculated for the 12 month follow-up with PRN treatment. Variability was expressed as standard deviation (SD). RESULTS Visual acuity (VA) improved from a mean ETDRS letter score of 61.6 (SD 10.8) at baseline to 68.0 (SD 10.2, +6.4 letters) at month 3 and increased further to 74.7 (SD 9.0, +13.1 letters from baseline) at month 12. The 15 patients who have completed the study by October 2010 showed maintenance of the VA improvement. Retinal thickness of the central foveal subfield improved from a mean value of 366?m(baseline) to 253?m(month 3), well maintained thereafter. Mean number of injections was 8.8 (SD 3.5) per 12 months of follow-up (after 3 loading doses), ranging from 0 to 12, with mean individual treatment-recurrence intervals ranging from 28 to >365 days (mean 58 days). Intraindividual variability of treatment-recurrence intervals, measured as SD of the individual intervals, was 7.1days as a mean value(range 1.7 ? 22.6 days) for the 33 patients with more than 1 injection during follow-up. SD was higher for longer intervals of an individual patient. It ranged within 20% of the mean intra-individual interval for 30 patients(91%) and within 15% for 21 patients(64%). The first interval was within 1 week of the mean intra-individual interval in 64% of patients and within 2 weeks in 89% of patients.CONCLUSIONS:The majority of AMD patients showed a relatively stable rhythm for PRN injections of intravitreal ranibizumab after initial loading phase, associated with excellent functional and anatomical results. The initial interval between last loading dose and first recurrence may have a predictive value for further need of treatment, therefore potentially facilitating follow-up and patient care.

Public-domain software for root image analysis

In the search for high efficiency in root studies, computational systems have been developed to analyze digital images. ImageJ and Safira are public-domain systems that may be used for image analysis of washed roots. However, differences in root properties measured using ImageJ and Safira are supposed. This study compared values of root length and surface area obtained with public-domain systems with values obtained by a reference method. Root samples were collected in a banana plantation in an area of a shallower Typic Carbonatic Haplic Cambisol (CXk), and an area of a deeper Typic Haplic Ta Eutrophic Cambisol (CXve), at six depths in five replications. Root images were digitized and the systems ImageJ and Safira used to determine root length and surface area. The line-intersect method modified by Tennant was used as reference; values of root length and surface area measured with the different systems were analyzed by Pearson's correlation coefficient and compared by the confidence interval and t-test. Both systems ImageJ and Safira had positive correlation coefficients with the reference method for root length and surface area data in CXk and CXve. The correlation coefficient ranged from 0.54 to 0.80, with lowest value observed for ImageJ in the measurement of surface area of roots sampled in CXve. The IC (95 %) revealed that root length measurements with Safira did not differ from that with the reference method in CXk (-77.3 to 244.0 mm). Regarding surface area measurements, Safira did not differ from the reference method for samples collected in CXk (-530.6 to 565.8 mm²) as well as in CXve (-4231 to 612.1 mm²). However, measurements with ImageJ were different from those obtained by the reference method, underestimating length and surface area in samples collected in CXk and CXve. Both ImageJ and Safira allow an identification of increases or decreases in root length and surface area. However, Safira results for root length and surface area are closer to the results obtained with the reference method.

A Cell Permeable Rasgap-derived Peptide Sensitizes Cancer Cells To Radiotherapy

Purpose/Objective(s): Radiotherapy is an effective treatment modality against cancer. Despite recent technical progresses in radiation delivery precision, toxicity to healthy tissues remains the main limiting factor. RasGAP is a regulator of the Ras and Rho pathway; it has either a pro- or anti-apoptotic activity depending on the level of caspase expressed in the cell. The RasGAP derived peptide: TAT-RasGAP317 - 326 is the minimal sequence known to sensitize cancer cells, but not healthy cells, to genotoxin-induced apoptosis. In this study the TAT-RasGAP317 - 326 radio-sensitizing effect was tested in vitro and in vivo.Materials/Methods: Two weeks clonogenic forming assays with 5 human cancer cells (PANC-1, HCT116, U87, U251 and HeLa) and a non tumorigenic cell line (HaCaT) were performed. Cells were exposed to 0, 1, 2 and 4 Gy with or without 20 mMTAT-RasGAP317 - 326. Twenty mMTAT peptide was also used as control. TAT-RasGAP317 - 326 effect was also tested in tumor xenograft mouse models. Mice bearing HCT116 tumors (WT or p53 mutant) received 1.65 mg/kg TAT-RasGAP317 - 326 i.p. injected and were locally irradiated for 10 days with 3 Gy. Tumor volume was then followed during a minimum of 20 days. Control mice were treated with a single modality, either with TAT-RasGAP317 - 326 or with radiotherapy.Results: At all the tested radiation doses TAT-RasGAP317 - 326 showed a significant supra additive radio-sensitizing effect on all the tested tumor cell lines. Furthermore, it showed no sensitizing effect on the non tumorigenic cell line. In vivo, TAT-RasGAP317 - 326 also showed a significantly radio-sensitizing effect as shown by a significant higher reduction in tumor volume as much as by a significant tumor growth delay.Conclusions: Taken together our data suggest that TAT-RasGAP317 - 326 has a radio-sensitizing effect on in vivo and in vitro tumors without any effect on healthy tissues. Therefore TAT-RasGAP317 - 326 should be considered as a novel and attractive sensitizer compound allowing an improvement of the therapeutic interval.

Advanced Kernel Methods For Remote Sensing Image Classification

Résumé Suite aux recentes avancées technologiques, les archives d'images digitales ont connu une croissance qualitative et quantitative sans précédent. Malgré les énormes possibilités qu'elles offrent, ces avancées posent de nouvelles questions quant au traitement des masses de données saisies. Cette question est à la base de cette Thèse: les problèmes de traitement d'information digitale à très haute résolution spatiale et/ou spectrale y sont considérés en recourant à des approches d'apprentissage statistique, les méthodes à noyau. Cette Thèse étudie des problèmes de classification d'images, c'est à dire de catégorisation de pixels en un nombre réduit de classes refletant les propriétés spectrales et contextuelles des objets qu'elles représentent. L'accent est mis sur l'efficience des algorithmes, ainsi que sur leur simplicité, de manière à augmenter leur potentiel d'implementation pour les utilisateurs. De plus, le défi de cette Thèse est de rester proche des problèmes concrets des utilisateurs d'images satellite sans pour autant perdre de vue l'intéret des méthodes proposées pour le milieu du machine learning dont elles sont issues. En ce sens, ce travail joue la carte de la transdisciplinarité en maintenant un lien fort entre les deux sciences dans tous les développements proposés. Quatre modèles sont proposés: le premier répond au problème de la haute dimensionalité et de la redondance des données par un modèle optimisant les performances en classification en s'adaptant aux particularités de l'image. Ceci est rendu possible par un système de ranking des variables (les bandes) qui est optimisé en même temps que le modèle de base: ce faisant, seules les variables importantes pour résoudre le problème sont utilisées par le classifieur. Le manque d'information étiquétée et l'incertitude quant à sa pertinence pour le problème sont à la source des deux modèles suivants, basés respectivement sur l'apprentissage actif et les méthodes semi-supervisées: le premier permet d'améliorer la qualité d'un ensemble d'entraînement par interaction directe entre l'utilisateur et la machine, alors que le deuxième utilise les pixels non étiquetés pour améliorer la description des données disponibles et la robustesse du modèle. Enfin, le dernier modèle proposé considère la question plus théorique de la structure entre les outputs: l'intègration de cette source d'information, jusqu'à présent jamais considérée en télédétection, ouvre des nouveaux défis de recherche. Advanced kernel methods for remote sensing image classification Devis Tuia Institut de Géomatique et d'Analyse du Risque September 2009 Abstract The technical developments in recent years have brought the quantity and quality of digital information to an unprecedented level, as enormous archives of satellite images are available to the users. However, even if these advances open more and more possibilities in the use of digital imagery, they also rise several problems of storage and treatment. The latter is considered in this Thesis: the processing of very high spatial and spectral resolution images is treated with approaches based on data-driven algorithms relying on kernel methods. In particular, the problem of image classification, i.e. the categorization of the image's pixels into a reduced number of classes reflecting spectral and contextual properties, is studied through the different models presented. The accent is put on algorithmic efficiency and the simplicity of the approaches proposed, to avoid too complex models that would not be used by users. The major challenge of the Thesis is to remain close to concrete remote sensing problems, without losing the methodological interest from the machine learning viewpoint: in this sense, this work aims at building a bridge between the machine learning and remote sensing communities and all the models proposed have been developed keeping in mind the need for such a synergy. Four models are proposed: first, an adaptive model learning the relevant image features has been proposed to solve the problem of high dimensionality and collinearity of the image features. This model provides automatically an accurate classifier and a ranking of the relevance of the single features. The scarcity and unreliability of labeled. information were the common root of the second and third models proposed: when confronted to such problems, the user can either construct the labeled set iteratively by direct interaction with the machine or use the unlabeled data to increase robustness and quality of the description of data. Both solutions have been explored resulting into two methodological contributions, based respectively on active learning and semisupervised learning. Finally, the more theoretical issue of structured outputs has been considered in the last model, which, by integrating outputs similarity into a model, opens new challenges and opportunities for remote sensing image processing.

Influence of operator experience on performance of ultrasound-guided percutaneous liver biopsy.

The purpose was to evaluate the influence of radiologist's experience on the diagnostic yield and complications of a percutaneous liver biopsy (PLB) method. Six hundred patients underwent an ultrasound-guided PLB by an inexperienced operator in 25.2% of cases (experience of less than 15 percutaneous liver biopsies performed alone--group I) or by an experienced operator (experience of more than 150 percutaneous liver biopsies--group II). The two groups were well-matched with respect to sex, age, percentage with viral hepatitis without histological cirrhosis, number of needle passes, history of liver biopsy and pain before the biopsy. A histological diagnosis was available in 97.3% of cases without any significant difference between the two groups ( P=0.25). However, group II samples were significantly longer and contained more portal tracts ( P=0.01). Pain was mild immediately and 6 h after the biopsy, without significant difference between both groups. Eight vasovagal reactions (five in group II) and one arteriobiliary fistula (in group II) occurred. With the method of PLB used for this study, operator's experience did not influence either the final histological diagnosis or the degree of pain suffered.

ZHARP: three-dimensional motion tracking from a single image plane.

Three-dimensional imaging and quantification of myocardial function are essential steps in the evaluation of cardiac disease. We propose a tagged magnetic resonance imaging methodology called zHARP that encodes and automatically tracks myocardial displacement in three dimensions. Unlike other motion encoding techniques, zHARP encodes both in-plane and through-plane motion in a single image plane without affecting the acquisition speed. Postprocessing unravels this encoding in order to directly track the 3-D displacement of every point within the image plane throughout an entire image sequence. Experimental results include a phantom validation experiment, which compares zHARP to phase contrast imaging, and an in vivo study of a normal human volunteer. Results demonstrate that the simultaneous extraction of in-plane and through-plane displacements from tagged images is feasible.