Simultaneous detection of aneuploidies for chromosomes 4, 6, 10 and 17 by automated four colour I-FISH in high hyperdiploid acute lymphoblastic leukemia : diagnostic assessment, clonal heterogeneity and chromosomal instability in adults

SummarySimultaneous detection of aneuploidies for chromosomes 4, 6,10 and 17 by automated four color l-FISH in high hyperdiploid acute lymphoblastic leukemia: diagnostic assessment, clonal heterogeneity and chromosomal instability in adultsAnna Talamo BlandinService de Génétique Médicale, Unité de Cytogénétique du Cancer, CHUVAcute lymphoblastic leukemia (ALL) is a malignant hemopathy characterized by the accumulation of the immature lymphoid cells in the bone marrow and, most often, in the peripheral blood. ALL is a heterogeneous disease with distinct biological and prognostic entities. At diagnosis, cytogenetic and molecular findings constitute important and independent prognostic factors. High hyperdiploidy with 51-67 chromosomes (HeH), one of the largest cytogenetic subsets of ALL, in childhood particularly, is generally associated with a relatively favorable outcome. Chromosome gain is nonrandom, extracopies of some chromosome occurring more frequently than those of others. Concurrent presence of trisomy for chromosomes 4, 10 and 17 confers an especially good prognosis. The first aim of our work was to develop an automated four color interphase fluorescence in situ hybridization (l-FISH) methodology and to assess its ability to detect concurrent aneuploidies 4, 6, 10 and 17 in 10 ALL patients. Various combinations of aneuploidies were identified. All clones detected by conventional cytogenetics were also observed by l-FISH. However, in all patients, l-FISH revealed numerous additional abnormal clones, leading to a high level of clonal heterogeneity. Our second aim has been to investigate the nature and origin of this clonal heterogeneity and to test for the presence of chromosome instability (CIN) in HeH ALL at initial presentation. Ten HeH ALL and 10 non-HeH ALL patients were analysed by four colour l-FISH and numerical CIN values were determined for all four chromosomes together and for each chromosome and patient group, an original approach in ALL. CIN values in HeH ALL proved to be much higher than#iose in non-HeH ALL, suggesting that numerical CIN may be at the origin of the high level of clonal heterogeneity revealed by l-FISH. Our third aim has been to study the evolution of these cytogenetic features during the course of the disease in 10 HeH ALL patients. Clonal heterogeneity was also observed again during disease progression, particularly at relapse. Clones detected at initial presentation generally reappeared in relapse, in most cases with newly generated ones. A significant correlation between the number of abnormal clones and CIN suggested that the higher the instability, the larger the number of abnormal clones. Whereas clonal heterogeneity and its evolution most probably result from underlying chromosome instability, operating processes remain conjectural.RésuméLa leucémie lymphoblastique aiguë (LLA) est une hémopathie maligne qui résulte de l'accumulationde cellules lymphoïdes immatures dans la moelle osseuse, et, le plus souvent, dans le sangpériphérique également. La LLA est une affection hétérogène au sein de laquelle se distinguentplusieurs entités biologiques et pronostiques. Les données cytogénétiques et moléculaires font partieintégrante du diagnostic et jouent un rôle essentiel dans l'évaluation du pronostic. L'hyperdiploïdieélevée à 51-­67 chromosomes (HeH), relativement fréquente, en particulier chez l'enfant, s'associe àun pronostic favorable. Le gain de chromosomes ne relève pas du hasard, certains chromosomesétant plus fréquemment impliqués que d'autres. La présence simultanée des trisomies 4, 6, et 17s'associe à un pronostic particulièrement bon. Le premier but du travail a été de développer uneméthode d'analyse automatique par hybridation in situ fluorescente interphasique (I-­FISH) à 4couleurs et de tester sa capacité à identifier la présence simultanée d'aneuploïdies 4, 6, 10 et 17 dans10 cas de LLA. Différentes combinaisons d'aneuploïdies ont été identifiées. Tous les clones détectéspar cytogénétique conventionnelle l'ont été par I-­FISH. Or, chez tous les patients, l'I-­FISH a révélé denombreux clones anormaux additionnels générant un degré élevé d'hétérogénéité clonale. Notredeuxième but a été d'investiguer la nature et l'origine de cette hétérogénéité et de tester la présenced'instabilité chromosomique (CIN) chez les patients avec une LLA HeH en presentation initiale. DixLLA HeH et 10 LLA non-­HeH ont été analysées par I-­FISH et les valeurs de CIN numérique ont étédéterminées pour les 4 chromosomes ensemble et pour chaque chromosome et groupe de patients,approche originale dans la LLA. Ces valeurs étant beaucoup plus élevées dans la LLA HeH que dansla LLA non-­HeH, elles favorisent l'hypothèse selon laquelle la CIN serait à l'origine de l'hétérogénéitéclonale révélée par I-­FISH. Le troisième but de notre travail a été d'étudier l'évolution de cescaractéristiques cytogénétiques au cours de la maladie dans 10 cas de LLA HeH. L'hétérogénéitéclonale a été retrouvée lors de la progression de la maladie, en particulier en rechute, où les clonesanormaux détectés en présentation initiale réapparaissent, généralement accompagnés de clonesnouveaux. La corrélation existant entre nombre de clones anormaux et valeurs de CIN suggère queplus l'instabilité est élevée, plus le nombre de clones anormaux est grand. Bien que l'hétérogénéitéclonale et son évolution résultent très probablement de l'instabilité chromosomique, les processus àl'oeuvre ne sont pas entièrement élucidés.

Improvement of the specificity of cancer detection by autofluorescence imaging in the tracheo-bronchial tree using backscattered violet light.

BACKGROUND: Autofluorescence bronchoscopy (AFB) is a highly sensitive tool for the detection of early bronchial cancers. However, its specificity remains limited due to primarily false positive results induced by hyperplasia, metaplasia and inflammation. We have investigated the potential of blue-violet backscattered light to eliminate false positive results during AFB in a clinical pilot study. METHODS: The diagnostic autofluorescence endoscopy (DAFE) system was equipped with a variable band pass filter in the imaging detection path. The backscattering properties of normal and abnormal bronchial mucosae were assessed by computing the contrast between the two tissue types for blue-violet wavelengths ranging between 410 and 490 nm in 12 patients undergoing routine DAFE examination. In a second study including 6 patients we used a variable long pass (LP) filter to determine the spectral design of the emission filter dedicated to the detection of this blue-violet light with the DAFE system. RESULTS: (Pre-)neoplastic mucosa showed a clear wavelength dependence of the backscattering properties of blue-violet light while the reflectivity of normal, metaplastic and hyperplastic autofluorescence positive mucosa was wavelength independent. CONCLUSIONS: Our results showed that the detection of blue-violet light has the potential to reduce the number of false positive results in AFB. In addition we determined the spectral design of the emission filter dedicated to the detection of this blue-violet light with the DAFE system.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

Hand detection in cluttered scene images using Fourier-Mellin invariant features

This paper proposes an automatic hand detection system that combines the Fourier-Mellin Transform along with other computer vision techniques to achieve hand detection in cluttered scene color images. The proposed system uses the Fourier-Mellin Transform as an invariant feature extractor to perform RST invariant hand detection. In a first stage of the system a simple non-adaptive skin color-based image segmentation and an interest point detector based on corners are used in order to identify regions of interest that contains possible matches. A sliding window algorithm is then used to scan the image at different scales performing the FMT calculations only in the previously detected regions of interest and comparing the extracted FM descriptor of the windows with a hand descriptors database obtained from a train image set. The results of the performed experiments suggest the use of Fourier-Mellin invariant features as a promising approach for automatic hand detection.

An embedded real-time red peach detection system based on an OV7670 camera, ARM Cortex-M4 processor and 3D Look-Up Tables

This work proposes the development of an embedded real-time fruit detection system for future automatic fruit harvesting. The proposed embedded system is based on an ARM Cortex-M4 (STM32F407VGT6) processor and an Omnivision OV7670 color camera. The future goal of this embedded vision system will be to control a robotized arm to automatically select and pick some fruit directly from the tree. The complete embedded system has been designed to be placed directly in the gripper tool of the future robotized harvesting arm. The embedded system will be able to perform real-time fruit detection and tracking by using a three-dimensional look-up-table (LUT) defined in the RGB color space and optimized for fruit picking. Additionally, two different methodologies for creating optimized 3D LUTs based on existing linear color models and fruit histograms were implemented in this work and compared for the case of red peaches. The resulting system is able to acquire general and zoomed orchard images and to update the relative tracking information of a red peach in the tree ten times per second.

Definition of linear color models in the RGB vector color space to detect red peaches in orchard images taken under natural illumination

This work proposes the detection of red peaches in orchard images based on the definition of different linear color models in the RGB vector color space. The classification and segmentation of the pixels of the image is then performed by comparing the color distance from each pixel to the different previously defined linear color models. The methodology proposed has been tested with images obtained in a real orchard under natural light. The peach variety in the orchard was the paraguayo (Prunus persica var. platycarpa) peach with red skin. The segmentation results showed that the area of the red peaches in the images was detected with an average error of 11.6%; 19.7% in the case of bright illumination; 8.2% in the case of low illumination; 8.6% for occlusion up to 33%; 12.2% in the case of occlusion between 34 and 66%; and 23% for occlusion above 66%. Finally, a methodology was proposed to estimate the diameter of the fruits based on an ellipsoidal fitting. A first diameter was obtained by using all the contour pixels and a second diameter was obtained by rejecting some pixels of the contour. This approach enables a rough estimate of the fruit occlusion percentage range by comparing the two diameter estimates.

Wood Volume Measurement Using Color Images

Tämä työ käsittelee puutukkien tilavuuden mittaamista värikonenäön avulla. Värikuvat on saatu Simpeleellä olevan metsäteollisuusyrityksen hiomosta. Työssä esitetään perusteellisesti matemaattinen teoria, joka liittyy käytettyihin kuvankäsittelymenetelmiin, kuten luokitteluun, kohinan poistoon ja tukkien segmentointiin. Esitetyt menetelmät implementointiin käytännössä ja eri menetelmillä saatuja tuloksia vertailtiin keskenään. Kuvankäsittelyalgoritmit on implementoitu Matlab 6.0:n avulla. Pääasiassa käytettiin uusinta Image Processing Toolboxia, joka on versio 3.0. Tämä työn näkökulma on pääasiassa käytäntöön soveltava, koska metsäteollsuus on korkealla tasolla Suomessa ja siellä on paljon alan yrityksiä, joissa tässä työssä kehitettyä menetelmää voidaan hyödyntää.

A screening method for detection of hexavalent chromium levels in soils

A rapid and low cost method to determine Cr(VI) in soils based upon alkaline metal extraction at room temperature is proposed as a semi-quantitative procedure to be performed in the field. A color comparison with standards with contents of Cr(VI) in the range of 10 to 150 mg kg-1 was used throughout. For the different types of soils studied, more than 75% of the fortified soluble Cr(VI) were recovered for all levels of spike tested for both the proposed and standard methods. Recoveries of 83 and 99% were obtained for the proposed and the standard methods, respectively, taking into account the analysis of a heavily contaminated soil sample.

A Technique for Digital Color Image Watermarking Using ICA

With the increase of use of digital media the need for the methods of multimedia protection becomes extremely important. The number of the solutions to the problem from encryption to watermarking is large and is growing every year. In this work digital image watermarking is considered, specifically a novel method of digital watermarking of color and spectral images. An overview of existing methods watermarking of color and grayscale images is given in the paper. Methods using independent component analysis (ICA) for detection and the ones using discrete wavelet transform (DWT) and discrete cosine transform (DCT) are considered in more detail. A novel method of watermarking proposed in this paper allows embedding of a color or spectral watermark image into color or spectral image consequently and successful extraction of the watermark out of the resultant watermarked image. A number of experiments have been performed on the quality of extraction depending on the parameters of the embedding procedure. Another set of experiments included the test of the robustness of the algorithm proposed. Three techniques have been chosen for that purpose: median filter, low-pass filter (LPF) and discrete cosine transform (DCT), which are a part of a widely known StirMark - Image Watermarking Robustness Test. The study shows that the proposed watermarking technique is fragile, i.e. watermark is altered by simple image processing operations. Moreover, we have found that the contents of the image to be watermarked do not affect the quality of the extraction. Mixing coefficients, that determine the amount of the key and watermark image in the result, should not exceed 1% of the original. The algorithm proposed has proven to be successful in the task of watermark embedding and extraction.

Evaluating perceptual maps of asymmetries for gait symmetry quantification and pathology detection

Le mouvement de la marche est un processus essentiel de l'activité humaine et aussi le résultat de nombreuses interactions collaboratives entre les systèmes neurologiques, articulaires et musculo-squelettiques fonctionnant ensemble efficacement. Ceci explique pourquoi une analyse de la marche est aujourd'hui de plus en plus utilisée pour le diagnostic (et aussi la prévention) de différents types de maladies (neurologiques, musculaires, orthopédique, etc.). Ce rapport présente une nouvelle méthode pour visualiser rapidement les différentes parties du corps humain liées à une possible asymétrie (temporellement invariante par translation) existant dans la démarche d'un patient pour une possible utilisation clinique quotidienne. L'objectif est de fournir une méthode à la fois facile et peu dispendieuse permettant la mesure et l'affichage visuel, d'une manière intuitive et perceptive, des différentes parties asymétriques d'une démarche. La méthode proposée repose sur l'utilisation d'un capteur de profondeur peu dispendieux (la Kinect) qui est très bien adaptée pour un diagnostique rapide effectué dans de petites salles médicales car ce capteur est d'une part facile à installer et ne nécessitant aucun marqueur. L'algorithme que nous allons présenter est basé sur le fait que la marche saine possède des propriétés de symétrie (relativement à une invariance temporelle) dans le plan coronal.

Automatic Optic Disc Boundary Extraction from Color Fundus Images

Efficient optic disc segmentation is an important task in automated retinal screening. For the same reason optic disc detection is fundamental for medical references and is important for the retinal image analysis application. The most difficult problem of optic disc extraction is to locate the region of interest. Moreover it is a time consuming task. This paper tries to overcome this barrier by presenting an automated method for optic disc boundary extraction using Fuzzy C Means combined with thresholding. The discs determined by the new method agree relatively well with those determined by the experts. The present method has been validated on a data set of 110 colour fundus images from DRION database, and has obtained promising results. The performance of the system is evaluated using the difference in horizontal and vertical diameters of the obtained disc boundary and that of the ground truth obtained from two expert ophthalmologists. For the 25 test images selected from the 110 colour fundus images, the Pearson correlation of the ground truth diameters with the detected diameters by the new method are 0.946 and 0.958 and, 0.94 and 0.974 respectively. From the scatter plot, it is shown that the ground truth and detected diameters have a high positive correlation. This computerized analysis of optic disc is very useful for the diagnosis of retinal diseases

Rotation Invariant Real-time Face Detection and Recognition System

In this report, a face recognition system that is capable of detecting and recognizing frontal and rotated faces was developed. Two face recognition methods focusing on the aspect of pose invariance are presented and evaluated - the whole face approach and the component-based approach. The main challenge of this project is to develop a system that is able to identify faces under different viewing angles in realtime. The development of such a system will enhance the capability and robustness of current face recognition technology. The whole-face approach recognizes faces by classifying a single feature vector consisting of the gray values of the whole face image. The component-based approach first locates the facial components and extracts them. These components are normalized and combined into a single feature vector for classification. The Support Vector Machine (SVM) is used as the classifier for both approaches. Extensive tests with respect to the robustness against pose changes are performed on a database that includes faces rotated up to about 40 degrees in depth. The component-based approach clearly outperforms the whole-face approach on all tests. Although this approach isproven to be more reliable, it is still too slow for real-time applications. That is the reason why a real-time face recognition system using the whole-face approach is implemented to recognize people in color video sequences.

Face Detection and Facial Feature Localization for multi-pose faces and complex backgroundimages

The objective of this thesis work, is to propose an algorithm to detect the faces in a digital image with complex background. A lot of work has already been done in the area of face detection, but drawback of some face detection algorithms is the lack of ability to detect faces with closed eyes and open mouth. Thus facial features form an important basis for detection. The current thesis work focuses on detection of faces based on facial objects. The procedure is composed of three different phases: segmentation phase, filtering phase and localization phase. In segmentation phase, the algorithm utilizes color segmentation to isolate human skin color based on its chrominance properties. In filtering phase, Minkowski addition based object removal (Morphological operations) has been used to remove the non-skin regions. In the last phase, Image Processing and Computer Vision methods have been used to find the existence of facial components in the skin regions.This method is effective on detecting a face region with closed eyes, open mouth and a half profile face. The experiment’s results demonstrated that the detection accuracy is around 85.4% and the detection speed is faster when compared to neural network method and other techniques.

Why are fruits colorful? The relative importance of achromatic and chromatic contrasts for detection by birds

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

New signature for color octet pseudoscalars at the CERN LHC

Color octet (pseudo)scalars, if they exist, will be copiously produced at the CERN Large Hadron Collider (LHC). However, their detection can become a very challenging task. In particular, if their decay into a pair of top quarks is kinematically forbidden, the main decay channel would be into two jets, with a very large background. In this brief report we explore the possibility of using anomaly-induced decays of the color octet pseudoscalars into gauge bosons to find them at the LHC.