Proceedings of the second "international Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST'14)

The implicit objective of the biennial "international - Traveling Workshop on Interactions between Sparse models and Technology" (iTWIST) is to foster collaboration between international scientific teams by disseminating ideas through both specific oral/poster presentations and free discussions. For its second edition, the iTWIST workshop took place in the medieval and picturesque town of Namur in Belgium, from Wednesday August 27th till Friday August 29th, 2014. The workshop was conveniently located in "The Arsenal" building within walking distance of both hotels and town center. iTWIST'14 has gathered about 70 international participants and has featured 9 invited talks, 10 oral presentations, and 14 posters on the following themes, all related to the theory, application and generalization of the "sparsity paradigm": Sparsity-driven data sensing and processing; Union of low dimensional subspaces; Beyond linear and convex inverse problem; Matrix/manifold/graph sensing/processing; Blind inverse problems and dictionary learning; Sparsity and computational neuroscience; Information theory, geometry and randomness; Complexity/accuracy tradeoffs in numerical methods; Sparsity? What's next?; Sparse machine learning and inference.Comment: 69 pages, 24 extended abstracts, iTWIST'14 website: http://sites.google.com/site/itwist1

New implementations of phase-contrast imaging

Phase-contrast imaging is a method of imaging widely used in biomedical research and applications. It is a label-free method that exploits intrinsic differences in the refractive index of different tissues to differentiate between biological structures under analysis. The basic principle of phase-contrast imaging has inspired a lot of implementations that are suited for different applications. This thesis explores multiple novel implementations of phase-contrast imaging in the following order. 1, We combined scanning Oblique Back-illumination Microscope (sOBM) and confocal microscope to produce phase and fluorescence contrast images in an endomicroscopy configuration. This dual-modality design provides co-registered, complementary labeled and unlabeled contrast of the sample. We further miniaturized the probe by dispensing the two optical fibers in our old design. And we presented proof of principle demonstrations with ex-vivo mouse colon tissue. 2, Then we explored sOBM-based phase and amplitude contrast imaging under different wavelengths. Hyperspectral imaging is achieved by multiplexing a wide-range supercontinuum laser with a Michaelson interferometer (similar to Fourier transform spectroscopy). It features simultaneous acquisition of hyperspectral phase and amplitude images with arbitrarily thick scattering biological samples. Proof-of-principle demonstrations are presented with chorioallantoic membrane of a chick embryo, illustrating the possibility of high-resolution hemodynamics imaging in thick tissue. 3, We focused on increasing the throughput of flow cytometry with principle of phase-contrast imaging and compressive sensing. By utilizing the linearity of scattered patterns under partially coherent illumination, our cytometer can detect multiple objects in the same field of view. By utilizing an optimized matched filter on pupil plane, it also provides increased information capacity of each measurement without sacrificing speed. We demonstrated a throughput of over 10,000 particles/s with accuracy over 91% in our results. 4, A fourth part, which describes the principle and preliminary results of a computational fluorescence endomicroscope is also included. It uses a numerical method to achieve sectioning effect and renders a pseudo-3D image stack with a single shot. The results are compared with true-3D image stack acquired with a confocal microscope

Biomedical Applications of Mid-Infrared Spectroscopic Imaging and Multivariate Data Analysis: Contribution to the Understanding of Diabetes Pathogenesis

Diabetic retinopathy (DR) is a microvascular complication of diabetes and a leading cause of adult vision loss. Although a great deal of progress has been made in ophthalmological examinations and clinical approaches to detect the signs of retinopathy in patients with diabetes, there still remain outstanding questions regarding the molecular and biochemical changes involved. To discover the biochemical mechanisms underlying the development and progression of changes in the retina as a result of diabetes, a more comprehensive understanding of the bio-molecular processes, in individual retinal cells subjected to hyperglycemia, is required. Animal models provide a suitable resource for temporal detection of the underlying pathophysiological and biochemical changes associated with DR, which is not fully attainable in human studies. In the present study, I aimed to determine the nature of diabetes-induced, highly localized biochemical changes in the retinal tissue from Ins2Akita/+ (Akita/+; a model of Type I diabetes) male mice with different duration of diabetes. Employing label-free, spatially resolved Fourier transform infrared (FT-IR) imaging engaged with chemometric tools enabled me to identify temporal-dependent reproducible biomarkers of the diabetic retinal tissue from mice with 6 or 12 weeks, and 6 or 10 months of diabetes. I report, for the first time, the origin of molecular changes in the biochemistry of individual retinal layers with different duration of diabetes. A robust classification between distinctive retinal layers - namely photoreceptor layer (PRL), outer plexiform layer (OPL), inner nuclear layer (INL), and inner plexiform layer (IPL) - and associated temporal-dependent spectral biomarkers, were delineated. Spatially-resolved super resolution chemical images revealed oxidative stress-induced structural and morphological alterations within the nucleus of the photoreceptors. Comparison among the PRL, OPL, INL, and IPL suggested that the photoreceptor layer is the most susceptible layer to the oxidative stress with short-duration of diabetes. Moreover, for the first time, we present the temporal-dependent molecular alterations for the PRL, OPL, INL, and IPL from Akita/+ mice, with progression of diabetes. These findings are potentially important and may be of particular benefit in understanding the molecular and biological activity of retinal cells during oxidative stress in diabetes. Our integrating paradigm provides a new conceptual framework and a significant rationale for a better understanding of the molecular and cellular mechanisms underlying the development and progression of DR. This approach may yield alternative and potentially complimentary methods for the assessment of diabetes changes. It is expected that the conclusions drawn from this work will bridge the gap in our knowledge regarding the biochemical mechanisms of the DR and address some critical needs in the biomedical community

Hyperspectral Imaging and Their Applications in the Nondestructive Quality Assessment of Fruits and Vegetables

Over the past decade, hyperspectral imaging has been rapidly developing and widely used as an emerging scientific tool in nondestructive fruit and vegetable quality assessment. Hyperspectral imaging technique integrates both the imaging and spectroscopic techniques into one system, and it can acquire a set of monochromatic images at almost continuous hundreds of thousands of wavelengths. Many researches based on spatial image and/or spectral image processing and analysis have been published proposing the use of hyperspectral imaging technique in the field of quality assessment of fruits and vegetables. This chapter presents a detailed overview of the introduction, latest developments and applications of hyperspectral imaging in the nondestructive assessment of fruits and vegetables. Additionally, the principal components, basic theories, and corresponding processing and analytical methods are also reported in this chapter

Application of artificial vision algorithms to images of microscopy and spectroscopy for the improvement of cancer diagnosis

El diagnóstico final de la mayoría de tipos de cáncer lo realiza un médico experto en anatomía patológica que examina muestras tisulares o celulares sospechosas extraídas del paciente. Actualmente, esta evaluación depende en gran medida de la experiencia del médico y se lleva a cabo de forma cualitativa mediante técnicas de imagen tradicionales como la microscopía óptica. Esta tarea tediosa está sujeta a altos grados de subjetividad y da lugar a niveles de discordancia inadecuados entre diferentes patólogos, especialmente en las primeras etapas de desarrollo del cáncer. La espectroscopía infrarroja por Transformada de Fourier (siglas FTIR en inglés) es una tecnología ampliamente utilizada en la industria que recientemente ha demostrado una capacidad creciente para mejorar el diagnóstico de diferentes tipos de cáncer. Esta técnica aprovecha las propiedades del infrarrojo medio para excitar los modos vibratorios de los enlaces químicos que forman las muestras biológicas. La principal señal generada consiste en un espectro de absorción que informa sobre la composición química de la muestra iluminada. Los microespectrómetros FTIR modernos, compuestos por complejos componentes ópticos y detectores matriciales de alta sensibilidad, permiten capturar en un laboratorio de investigación común imágenes hiperespectrales de alta calidad que aúnan información química y espacial. Las imágenes FTIR son estructuras de datos ricas en información que se pueden analizar individualmente o junto con otras modalidades de imagen para realizar diagnósticos patológicos objetivos. Por lo tanto, esta técnica de imagen emergente alberga un alto potencial para mejorar la detección y la graduación del riesgo del paciente en el cribado y vigilancia de cáncer. Esta tesis estudia e implementa diferentes metodologías y algoritmos de los campos interrelacionados de procesamiento de imagen, visión por ordenador, aprendizaje automático, reconocimiento de patrones, análisis multivariante y quimiometría para el procesamiento y análisis de imágenes hiperespectrales FTIR. Estas imágenes se capturaron con un moderno microscopio FTIR de laboratorio a partir de muestras de tejidos y células afectadas por cáncer colorrectal y de piel, las cuales se prepararon siguiendo protocolos alineados con la práctica clínica actual. Los conceptos más relevantes de la espectroscopía FTIR se investigan profundamente, ya que deben ser comprendidos y tenidos en cuenta para llevar a cabo una correcta interpretación y tratamiento de sus señales especiales. En particular, se revisan y analizan diferentes factores fisicoquímicos que influyen en las mediciones espectroscópicas en el caso particular de muestras biológicas y pueden afectar críticamente su análisis posterior. Todos estos conceptos y estudios preliminares entran en juego en dos aplicaciones principales. La primera aplicación aborda el problema del registro o alineación de imágenes hiperespectrales FTIR con imágenes en color adquiridas con microscopios tradicionales. El objetivo es fusionar la información espacial de distintas muestras de tejido medidas con esas dos modalidades de imagen y centrar la discriminación en las regiones seleccionadas por los patólogos, las cuales se consideran más relevantes para el diagnóstico de cáncer colorrectal. En la segunda aplicación, la espectroscopía FTIR se lleva a sus límites de detección para el estudio de las entidades biomédicas más pequeñas. El objetivo es evaluar las capacidades de las señales FTIR para discriminar de manera fiable diferentes tipos de células de piel que contienen fenotipos malignos. Los estudios desarrollados contribuyen a la mejora de métodos de decisión objetivos que ayuden al patólogo en el diagnóstico final del cáncer. Además, revelan las limitaciones de los protocolos actuales y los problemas intrínsecos de la tecnología FTIR moderna, que deberían abordarse para permitThe final diagnosis of most types of cancers is performed by an expert clinician in anatomical pathology who examines suspicious tissue or cell samples extracted from the patient. Currently, this assessment largely relies on the experience of the clinician and is accomplished in a qualitative manner by means of traditional imaging techniques, such as optical microscopy. This tedious task is subject to high degrees of subjectivity and gives rise to suboptimal levels of discordance between different pathologists, especially in early stages of cancer development. Fourier Transform infrared (FTIR) spectroscopy is a technology widely used in industry that has recently shown an increasing capability to improve the diagnosis of different types of cancer. This technique takes advantage of the ability of mid-infrared light to excite the vibrational modes of the chemical bonds that form the biological samples. The main generated signal consists of an absorption spectrum that informs of the chemical composition of the illuminated specimen. Modern FTIR microspectrometers, composed of complex optical components and high-sensitive array detectors, allow the acquisition of high-quality hyperspectral images with spatially-resolved chemical information in a common research laboratory. FTIR images are information-rich data structures that can be analysed alone or together with other imaging modalities to provide objective pathological diagnoses. Hence, this emerging imaging technique presents a high potential to improve the detection and risk stratification in cancer screening and surveillance. This thesis studies and implements different methodologies and algorithms from the related fields of image processing, computer vision, machine learning, pattern recognition, multivariate analysis and chemometrics for the processing and analysis of FTIR hyperspectral images. Those images were acquired with a modern benchtop FTIR microspectrometer from tissue and cell samples affected by colorectal and skin cancer, which were prepared by following protocols close to the current clinical practise. The most relevant concepts of FTIR spectroscopy are thoroughly investigated, which ought to be understood and considered to perform a correct interpretation and treatment of its special signals. In particular, different physicochemical factors are reviewed and analysed, which influence the spectroscopic measurements for the particular case of biological samples and can critically affect their later analysis. All these knowledge and preliminary studies come into play in two main applications. The first application tackles the problem of registration or alignment of FTIR hyperspectral images with colour images acquired with traditional microscopes. The aim is to fuse the spatial information of distinct tissue samples measured by those two imaging modalities and focus the discrimination on regions selected by the pathologists, which are meant to be the most relevant areas for the diagnosis of colorectal cancer. In the second application, FTIR spectroscopy is pushed to their limits of detection for the study of the smallest biomedical entities. The aim is to assess the capabilities of FTIR signals to reliably discriminate different types of skin cells containing malignant phenotypes. The developed studies contribute to the improvement of objective decision methods to support the pathologist in the final diagnosis of cancer. In addition, they reveal the limitations of current protocols and intrinsic problems of modern FTIR technology, which should be tackled in order to enable its transference to anatomical pathology laboratories in the future.El diagnòstic final de la majoria de tipus de càncer ho realitza un metge expert en anatomia patològica que examina mostres tissulars o cel¿lulars sospitoses extretes del pacient. Actualment, aquesta avaluació depèn en gran part de l'experiència del metge i es porta a terme de forma qualitativa mitjançant tècniques d'imatge tradicionals com la microscòpia òptica. Aquesta tasca tediosa està subjecta a alts graus de subjectivitat i dóna lloc a nivells de discordança inadequats entre diferents patòlegs, especialment en les primeres etapes de desenvolupament del càncer. L'espectroscòpia infraroja per Transformada de Fourier (sigles FTIR en anglès) és una tecnologia àmpliament utilitzada en la indústria que recentment ha demostrat una capacitat creixent per millorar el diagnòstic de diferents tipus de càncer. Aquesta tècnica aprofita les propietats de l'infraroig mitjà per excitar els modes vibratoris dels enllaços químics que formen les mostres biològiques. El principal senyal generat consisteix en un espectre d'absorció que informa sobre la composició química de la mostra il¿luminada. Els microespectrómetres FTIR moderns, compostos per complexos components òptics i detectors matricials d'alta sensibilitat, permeten capturar en un laboratori d'investigació comú imatges hiperespectrals d'alta qualitat que uneixen informació química i espacial. Les imatges FTIR són estructures de dades riques en informació que es poden analitzar individualment o juntament amb altres modalitats d'imatge per a realitzar diagnòstics patològics objectius. Per tant, aquesta tècnica d'imatge emergent té un alt potencial per a millorar la detecció i la graduació del risc del pacient en el cribratge i vigilància de càncer. Aquesta tesi estudia i implementa diferents metodologies i algoritmes dels camps interrelacionats de processament d'imatge, visió per ordinador, aprenentatge automàtic, reconeixement de patrons, anàlisi multivariant i quimiometria per al processament i anàlisi d'imatges hiperespectrals FTIR. Aquestes imatges es van capturar amb un modern microscopi FTIR de laboratori a partir de mostres de teixits i cèl¿lules afectades per càncer colorectal i de pell, les quals es van preparar seguint protocols alineats amb la pràctica clínica actual. Els conceptes més rellevants de l'espectroscòpia FTIR s'investiguen profundament, ja que han de ser compresos i tinguts en compte per dur a terme una correcta interpretació i tractament dels seus senyals especials. En particular, es revisen i analitzen diferents factors fisicoquímics que influeixen en els mesuraments espectroscòpiques en el cas particular de mostres biològiques i poden afectar críticament la seua anàlisi posterior. Tots aquests conceptes i estudis preliminars entren en joc en dues aplicacions principals. La primera aplicació aborda el problema del registre o alineació d'imatges hiperespectrals FTIR amb imatges en color adquirides amb microscopis tradicionals. L'objectiu és fusionar la informació espacial de diferents mostres de teixit mesurades amb aquestes dues modalitats d'imatge i centrar la discriminació en les regions seleccionades pels patòlegs, les quals es consideren més rellevants per al diagnòstic de càncer colorectal. En la segona aplicació, l'espectroscòpia FTIR es porta als seus límits de detecció per a l'estudi de les entitats biomèdiques més xicotetes. L'objectiu és avaluar les capacitats dels senyals FTIR per discriminar de manera fiable diferents tipus de cèl¿lules de pell que contenen fenotips malignes. Els estudis desenvolupats contribueixen a la millora de mètodes de decisió objectius que ajuden el patòleg en el diagnòstic final del càncer. A més, revelen les limitacions dels protocols actuals i els problemes intrínsecs de la tecnologia FTIR moderna, que haurien d'abordar per permetre la seva transferència als laboratoris d'anatomia patològica en el futur.Peñaranda Gómez, FJ. (2018). Application of artificial vision algorithms to images of microscopy and spectroscopy for the improvement of cancer diagnosis [Tesis doctoral no publicada]. Universitat Politècnica de València. https://doi.org/10.4995/Thesis/10251/99748TESI

Reconstruction algorithms for multispectral diffraction imaging

Thesis (Ph.D.)--Boston UniversityIn conventional Computed Tomography (CT) systems, a single X-ray source spectrum is used to radiate an object and the total transmitted intensity is measured to construct the spatial linear attenuation coefficient (LAC) distribution. Such scalar information is adequate for visualization of interior physical structures, but additional dimensions would be useful to characterize the nature of the structures. By imaging using broadband radiation and collecting energy-sensitive measurement information, one can generate images of additional energy-dependent properties that can be used to characterize the nature of specific areas in the object of interest. In this thesis, we explore novel imaging modalities that use broadband sources and energy-sensitive detection to generate images of energy-dependent properties of a region, with the objective of providing high quality information for material component identification. We explore two classes of imaging problems: 1) excitation using broad spectrum sub-millimeter radiation in the Terahertz regime and measure- ment of the diffracted Terahertz (THz) field to construct the spatial distribution of complex refractive index at multiple frequencies; 2) excitation using broad spectrum X-ray sources and measurement of coherent scatter radiation to image the spatial distribution of coherent-scatter form factors. For these modalities, we extend approaches developed for multimodal imaging and propose new reconstruction algorithms that impose regularization structure such as common object boundaries across reconstructed regions at different frequencies. We also explore reconstruction techniques that incorporate prior knowledge in the form of spectral parametrization, sparse representations over redundant dictionaries and explore the advantage and disadvantages of these techniques in terms of image quality and potential for accurate material characterization. We use the proposed reconstruction techniques to explore alternative architectures with reduced scanning time and increased signal-to-noise ratio, including THz diffraction tomography, limited angle X-ray diffraction tomography and the use of coded aperture masks. Numerical experiments and Monte Carlo simulations were conducted to compare performances of the developed methods, and validate the studied architectures as viable options for imaging of energy-dependent properties

Applications Of Microspectroscopy, Hyperspectral Chemical Imaging And Fluorescence Microscopy In Chemistry, Biochemistry, Biotechnology, Molecular And Cell Biology

Chemical imaging is a technique for the simultaneous measurement of spectra (chemical information) and images or pictures (spatial information)^1,2^. The technique is most often applied to either solid or gel samples, and has applications in chemistry, biology^3-8^, medicine^9,10^, pharmacy^11^ (see also for example: Chemical Imaging Without Dyeing), food science, Food Physical Chemistry, Biotechnology^12,13^, Agriculture and industry. NIR, IR and Raman chemical imaging is also referred to as hyperspectral, spectroscopic, spectral or multi-spectral imaging (also see micro-spectroscopy). However, other ultra-sensitive and selective, chemical imaging techniques are also in use that involve either UV-visible or fluorescence microspectroscopy

Fingerprint multiplex CARS at high speed based on supercontinuum generation in bulk media and deep learning spectral denoising

We introduce a broadband coherent anti-Stokes Raman scattering (CARS) microscope based on a 2-MHz repetition rate ytterbium laser generating 1035-nm high-energy (≈µJ level) femtosecond pulses. These features of the driving laser allow producing broadband red-shifted Stokes pulses, covering the whole fingerprint region (400-1800 cm-1), employing supercontinuum generation in a bulk crystal. Our system reaches state-of-the-art acquisition speed (<1 ms/pixel) and unprecedented sensitivity of ≈14.1 mmol/L when detecting dimethyl sulfoxide in water. To further improve the performance of the system and to enhance the signal-to-noise ratio of the CARS spectra, we designed a convolutional neural network for spectral denoising, coupled with a post-processing pipeline to distinguish different chemical species of biological tissues