Toward data science in biophotonics: biomedical investigations-based study

Biophotonics aims to grasp and investigate the characteristics of biological samples based on their interaction with incident light. Over the past decades, numerous biophotonic technologies have been developed delivering various sorts of biological and chemical information from the studied samples. Such information is usually contained in high dimensional data that need to be translated into high-level information like disease biomarkers. This data translation is not straightforward, but it can be achieved using the advances in computer and data science. The scientific contributions presented in this thesis were established to cover two main aspects of data science in biophotonics: the design of experiments and the data-driven modeling and validation. For the design of experiment, the scientific contributions focus on estimating the sample size required for group differentiation and on evaluating the influence of experimental factors on unbalanced multifactorial designs. Both methods were designed for multivariate data and were checked on Raman spectral datasets. Thereafter, the automatic detection and identification of three diagnostic tasks were checked based on combining several image processing techniques with machine learning (ML) algorithms. In the first task, an improved ML pipeline to predict the antibiotic susceptibilities of E. coli bacteria was presented and evaluated based on bright-field microscopic images. Then, transfer learning-based classification of bladder cancer was demonstrated using blue light cystoscopic images. Finally, different ML techniques and validation strategies were combined to perform the automatic detection of breast cancer based on a small-sized dataset of nonlinear multimodal images. The obtained results exhibited the benefits of data science tools in improving the experimantal planning and the translation of biophotonic-associated data into high-level information for various biophotonic technologies

Artistic minimal rendering with lines and blocks

Many non-photorealistic rendering techniques exist to produce artistic effects from given images. Inspired by various artists, interesting effects can be produced by using a minimal rendering, where the minimum refers to the number of tones as well as the number and complexity of the primitives used for rendering. Our method is based on various computer vision techniques, and uses a combination of refined lines and blocks (potentially simplified), as well as a small number of tones, to produce abstracted artistic rendering with sufficient elements from the original image. We also considered a variety of methods to produce different artistic styles, such as colour and 2-tone drawings, and use semantic information to improve renderings for faces. By changing some intuitive parameters a wide range of visually pleasing results can be produced. Our method is fully automatic. We demonstrate the effectiveness of our method with extensive experiments and a user study

Snow cover detection from webcam images

Práce zkoumá možnosti využití webových kamer jakožto zdroje prostorových dat o výskytu sněhu. Cílem práce je navržení vhodné metody detekce sněhové pokrývky ze snímků webových kamer. Na vzorku snímků 6 webových kamer ČHMÚ je provedena detekce sněhové pokrývky metodami pixelové klasifikace. Je zkoumán vliv velikosti trénovacího souboru na přesnost klasifikace. Celková přesnost dosažená metodou SVM je 97,46 %. Dále je cílem navrhnout systém pro určení podílu sněhem pokrytého území. Vytvořený algoritmus se skládá z několika dílčích kroků: třídění a registrace snímků, detekce sněhu, zavedení souřadnicového systému, výpočtu velikosti zkoumané plochy a podílu sněhem pokrytého území. Navržený model je možné použít pro automatizované zpracování snímků různých webových kamer. Ze získaných denních hodnot podílu sněhem pokrytého území jsou vytvořeny křivky tání sněhové pokrývky. Výsledky jsou validovány pomocí dat vybraných stanic ČHMÚ. Navržený a parametrizovaný model potvrzuje možnost úspěšně využít webové kamery jako doplněk pozemního měření meteorologických stanic a pro validaci produktů dálkového průzkumu Země.This thesis deals with the possibility of using webcams as a source of spatial data for snow occurrence. The aim of this study is to propose a suitable method of snow cover detection from web camera images. From a sample of 6 webcams of the Czech Hydrometeorological Institute (CHMI) the snow cover is detected by pixel classification methods. The effect of training file size on the accuracy of classification is examined and the overall accuracy achieved by the SVM method was shown to be 97.46%. This study also aims to propose a system for determining the proportion of snow-covered areas. The algorithm consists of several sub-steps: filtering and registration of images, detection of snow, introduction of a coordinate system, calculation of the size of the surveyed area and the proportion of snow-covered area. The designed model can be used for automatic processing of images for various webcams. The melting curves of the snow cover are generated from the obtained daily values of the snow covered area. The results are validated using data from selected CHMI stations. The proposed and parameterized model confirms the possibility of successful use of webcams as a complement to ground measurement of meteorological stations and for the validation of remote sensing products.Department of Applied Geoinformatics and CartographyKatedra aplikované geoinformatiky a kartografiePřírodovědecká fakultaFaculty of Scienc

Une approche logicielle du traitement de la dyslexie : étude de modèles et applications

Neuropsychological disorders are widespread and generate real public health problems. In particular in our modern society, where written communication is ubiquitous, dyslexia can be extremely disabling. Nevertheless we can note that the diagnosis and remediation of this pathology are fastidious and lack of standardization. Unfortunately it seems inherent to the clinical characterization of dyslexia by exclusion, to the multitude of different practitioners involved in such treatment and to the lack of objectivity of some existing methods. In this respect, we decided to investigate the possibilities offered by modern computing to overcome these barriers. Indeed we have assumed that the democratization of computer systems and their computing power could make of them a perfect tool to alleviate the difficulties encountered in the treatment of dyslexia. This research has led us to study the techniques software as well as hardware, which can conduct to the development of an inexpensive and scalable system able to attend a beneficial and progressive changing of practices in this pathology field. With this project we put ourselves definitely in an innovative stream serving quality of care and aid provided to people with disabilities. Our work has been identifying different improvement areas that the use of computers enables. Then each of these areas could then be the subject of extensive research, modeling and prototype developments. We also considered the methodology for designing this kind of system as a whole. In particular our thoughts and these accomplishments have allowed us to define a software framework suitable for implementing a software platform that we called the PAMMA. This platform should theoretically have access to all the tools required for the flexible and efficient development of medical applications integrating business processes. In this way it is expected that this system allows the development of applications for caring dyslexic patients thus leading to a faster and more accurate diagnosis and a more appropriate and effective remediation. Of our innovation efforts emerge encouraging perspectives. However such initiatives can only be achieved within multidisciplinary collaborations with many functional, technical and financial means. Creating such a consortium seems to be the next required step to get a funding necessary for realizing a first functional prototype of the PAMMA, as well as its first applications. Some clinical studies may be conducted to prove undoubtedly the effectiveness of such an approach for treating dyslexia and eventually other neuropsychological disorders.Les troubles neuropsychologiques sont très répandus et posent de réels problèmes de santé publique. En particulier, dans notre société moderne où la communication écrite est omniprésente, la dyslexie peut s’avérer excessivement handicapante. On remarque néanmoins que le diagnostic et la remédiation de cette pathologie restent délicats et manquent d’uniformisation. Ceci semble malheureusement inhérent à la caractérisation clinique par exclusion de la dyslexie, à la multitude de praticiens différents impliqués dans une telle prise en charge ainsi qu’au manque d’objectivité de certaines méthodes existantes. A ce titre, nous avons décidé d’investiguer les possibilités offertes par l’informatique actuelle pour surmonter ces barrières. Effectivement, nous avons supposé que la démocratisation des systèmes informatiques et leur puissance de calcul pourraient en faire un outil de choix pour pallier les difficultés rencontrées lors de la prise en charge de la dyslexie. Cette recherche nous a ainsi mené à étudier les techniques, aussi bien logicielles que matérielles, pouvant conduire au développement d’un système bon marché et évolutif qui serait capable d’assister un changement bénéfique et progressif des pratiques qui entourent cette pathologie. Avec ce projet, nous nous plaçons définitivement dans un courant innovant au service de la qualité des soins et des aides apportées aux personnes souffrant d’un handicap. Notre travail a ainsi consisté à identifier différents axes d’amélioration que l’utilisation de l’outil informatique rend possible. Chacun de ces axes a alors pu faire l’objet de recherches exhaustives, de modélisations et de développements de prototypes. Nous avons également réfléchi à la méthodologie à mettre en œuvre pour concevoir un tel système dans sa globalité. En particulier, nos réflexions et ces différents accomplissements nous ont permis de définir un framework logiciel propice à l’implémentation d’une plate-forme logicielle que nous avons appelée la PAMMA. Cette plate-forme devrait théoriquement pouvoir disposer de tous les outils permettant le développement souple et efficace d’applications médicales intégrant des processus métiers. Il est ainsi attendu de ce système qu’il permette le développement d’applications, pour la prise en charges des patients dyslexiques, conduisant à un diagnostic plus rapide et plus précis ainsi qu’à une remédiation plus adaptée et plus efficace. De notre effort d’innovation ressortent des perspectives encourageantes. Cependant, ce type d’initiative ne peut se concrétiser qu’autour de collaborations pluridisciplinaires disposant de nombreux moyens fonctionnels, techniques et financiers. La constitution d’un tel consortium semble donc être la prochaine étape nécessaire à l’obtention des financements pour réaliser un premier prototype fonctionnel de la PAMMA, ainsi que de premières applications. Des études cliniques pourront être alors menées pour prouver indubitablement l’efficacité d’une telle approche dans le cadre de la prise en charge de la dyslexie, ainsi qu’éventuellement d’autres troubles neuropsychologiques