Joint segmentation and classification of retinal arteries/veins from fundus images

Objective Automatic artery/vein (A/V) segmentation from fundus images is required to track blood vessel changes occurring with many pathologies including retinopathy and cardiovascular pathologies. One of the clinical measures that quantifies vessel changes is the arterio-venous ratio (AVR) which represents the ratio between artery and vein diameters. This measure significantly depends on the accuracy of vessel segmentation and classification into arteries and veins. This paper proposes a fast, novel method for semantic A/V segmentation combining deep learning and graph propagation. Methods A convolutional neural network (CNN) is proposed to jointly segment and classify vessels into arteries and veins. The initial CNN labeling is propagated through a graph representation of the retinal vasculature, whose nodes are defined as the vessel branches and edges are weighted by the cost of linking pairs of branches. To efficiently propagate the labels, the graph is simplified into its minimum spanning tree. Results The method achieves an accuracy of 94.8% for vessels segmentation. The A/V classification achieves a specificity of 92.9% with a sensitivity of 93.7% on the CT-DRIVE database compared to the state-of-the-art-specificity and sensitivity, both of 91.7%. Conclusion The results show that our method outperforms the leading previous works on a public dataset for A/V classification and is by far the fastest. Significance The proposed global AVR calculated on the whole fundus image using our automatic A/V segmentation method can better track vessel changes associated to diabetic retinopathy than the standard local AVR calculated only around the optic disc.Comment: Preprint accepted in Artificial Intelligence in Medicin

Autocalibrage de séquences d'images thoracoscopiques

RÉSUMÉ Le développement considérable des techniques d’imagerie vidéo a permis d’explorer de nouvelles techniques de chirurgie dans le domaine médical et notamment celles de chirurgies minimalement invasives. La chirurgie minimalement invasive (sans pratiquer de larges incisions) permet de réduire les risques opératoires pour le patient puisque les instruments et la caméra sont introduits à travers de petites incisions. La caméra sert à visualiser le champ opératoire afin de guider l’intervention du chirurgien. Cependant, le chirurgien perd alors toute notion de contexte et de profondeur lors d’une opération, sa vision étant limitée à une séquence d’images 2D acquises par la caméra. C’est pourquoi un système d’assistance chirurgical pourrait faciliter ce type d’interventions. Des systèmes de navigation 3D sont en cours de développement pour assister le chirurgien dans les domaines de cardiologie et de neurochirurgie. Cependant, la plupart des systèmes de navigation 3D à la chirurgie de la colonne vertébrale sont destinés pour l’assistance des chirurgies classiques nécessitant de grandes ouvertures. De plus, ces systèmes requièrent un ensemble de marqueurs fixés sur les vertèbres afin de recaler un modèle 3D pré-opératoire avec des images per-opératoires. La procédure de fixation des marqueurs est non seulement invasive, compliquant davantage le protocole chirurgical, mais aussi ne peut pas être pratiquée lors d’une chirurgie minimalement invasive. Le but ultime de notre projet est de proposer un système d’assistance des chirurgies minimalement invasive de la colonne vertébrale reposant exclusivement sur l’information contenue dans la séquence d’images acquises par une caméra endoscopique insérée dans le thorax du patient à travers une petite incision.----------ABSTRACT The considerable expansion of video imaging techniques in recent years has opened the way toward exploring new surgical techniques in the medical field including minimally invasive surgery approaches. Minimally invasive surgery reduces the risk of an operation for the patient because the instruments and camera are inserted through small incisions. The camera is used to view the operative field to guide the surgeon’s intervention. However, the surgeon loses the notion of depth during such an operation, his vision being limited to a sequence of 2D images acquired by the camera. Therefore, a surgical assistance system could facilitate this type of intervention. 3D navigation systems are currently being developed to assist the surgeon in the fields of cardiology and neurosurgery. However, most 3D navigation systems for spine surgery are designed to assist conventional surgeries requiring large openings. In addition, these systems require a set of markers attached to the vertebrae to register a pre-operative 3D model with peroperative images. The procedure for setting the markers is not only invasive and thus complicates the surgical protocol but cannot be performed in a minimally invasive surgery. Therefore, the ultimate goal of our project is to provide a framework for assisting minimally invasive surgeries of the spine, based solely on information contained in the sequence of peroperative images acquired by an endoscopic camera inserted into the patient’s chest through a small incision . Our goal is thus to develop a self-autocalibration method for a sequence of thoracoscopic images acquired during a minimally invasive surgery of the spine. This will allow us to readjust a 3D pre-operative patient spine model to the images of the sequence in real time as the surgeon performs the operation. The thoracoscopic images will be repositioned in 3D space to allow the surgeon to move around the 3D model and thus facilitate the operation

Modélisation statistique des structures anatomiques de la rétine à partir d'images de fond d'oeil

L’examen non-invasif du fond d’oeil permet d’identifier sur la rétine les signes de nombreuses pathologies oculaires qui développent de graves symptômes pour le patient pouvant entraîner la cécité. Le réseau vasculaire rétinien peut de surcroît présenter des signes précurseurs de pathologies cardiovasculaires et cérébro-vasculaires. La rétine, où apparaissent ces pathologies, est constituée de plusieurs structures anatomiques dont la variabilité est importante au sein d’une population saine. Pour autant, les évaluations cliniques actuelles ne prennent pas en compte cette variabilité ce qui ne permet pas de détecter précocement ces pathologies. Ces évaluations se basent sur un ensemble restreint de mesures prélevées à partir de structures dont la segmentation manuelle est réalisable par les experts. De plus, elles sont basées sur un seuillage empirique déterminé par les cliniciens et appliqué sur chacune des mesures afin d’établir un diagnostic. Ainsi, les évaluations cliniques actuelles sont affectées par la grande variabilité des structures anatomiques de la rétine au sein de la population et elles n’évaluent pas les anomalies trop difficiles à mesurer manuellement. Dans ce contexte, il convient de proposer de nouvelles mesures cliniques qui tiennent compte de la variabilité normale à l’aide d’une modélisation statistique des structures anatomiques de la rétine. Cette modélisation statistique permet de mieux comprendre et identifier ce qui est normal et comment l’anatomie et ses attributs varient au sein d’une population saine. Cela permet ainsi d’identifier la présence de pathologies à l’aide de nouvelles mesures cliniques construites en tenant compte de la variabilité des attributs de l’anatomie. La modélisation statistique des structures anatomiques de la rétine est cependant difficile étant donné les variations morphologiques et topologiques de ces structures. Les changements morphologiques et topologiques du réseau vasculaire rétinien compliquent son analyse statistique ainsi que les outils de recalage, de segmentation et de représentation sémantique s’y appliquant. Les questions de recherches adressées dans cette thèse sont la production d’outils capables d’analyser la variabilité des structures anatomiques de la rétine et l’élaboration de nouvelles mesures cliniques tenant compte de la variabilité normale de ces structures. Pour répondre à ces questions de recherche, trois objectifs de recherche sont formulés. ----------ABSTRACT: Non-invasive retinal fundus examination allows clinicians to identify signs of many ocular conditions that develop critical symptoms affecting the patient and even leading to blindness. In addition, the retinal vascular network may present early signs of cardiovascular and cerebrovascular diseases. The retina, where these pathologies appear, is composed of several anatomical structures whose variability is considerable within a healthy population. Yet, current clinical evaluations do not take into account this variability, and this does not allow early detection of these pathologies. These evaluations are based on a limited set of measurements taken from structures whose manual segmentation is achievable by the experts. In addition, they are based on empirical thresholding determined by the clinicians and applied to each of the measurements to establish a diagnosis. Thus, current clinical assessments are affected by the large variability of anatomical structures of the retina within a healthy population and do not evaluate abnormalities that are too difficult to measure manually. In this context, it is advisable to propose new clinical measurements that take into account the normal variability using statistical modeling of the anatomical structures of the retina. Such a statistical modeling approach helps us to better understand and identify what is normal and how the anatomy and its attributes vary across a healthy population. This makes it possible to identify the presence of pathologies using new clinical measurements constructed by taking into account the variability of the anatomy’s attributes. Statistical modeling of the anatomical structures of the retina is difficult, however, given the morphological and topological variations of these structures. Morphological and topological changes in the retinal vascular network complicate its statistical analysis as well as the registration methods, segmentation and semantic representation applied to it. The research questions proposed in this thesis pertain to creating tools capable of analyzing the variability of the anatomical structures of the retina and proposing new clinical measures that take into account the normal variability of those structures. To answer these research questions, three research objectives are formulated

Uncertainty assessment of vessels width measurement from intensity profile model fitting in fundus images

Arteriolar-to-venular diameter ratio (AVR) is an important clinical measurement that allows to characterize retinal vascular abnormalities. A reliable AVR measurement requires accurate and reproducible width measurement. However, in order to measure the vessel width automatically, an approximation of the intensity profile is required by fitting a model. The aim of the proposed study is to assess the uncertainties introduced in the vessel width measurements when choosing a specific distribution as an intensity profile model. Different models are described and an automatic vessel width measurement procedure is presented. The uncertainty introduced by each model is evaluated by computing the standard deviation of the difference between the automatic and the manual measurements. The results show that the intensity profile model should be chosen according to the relative width of the targeted vessels

End-to-End Deep Learning Model for Cardiac Cycle Synchronization from Multi-View Angiographic Sequences

Dynamic reconstructions (3D+T) of coronary arteries could give important perfusion details to clinicians. Temporal matching of the different views, which may not be acquired simultaneously, is a prerequisite for an accurate stereo-matching of the coronary segments. In this paper, we show how a neural network can be trained from angiographic sequences to synchronize different views during the cardiac cycle using raw x-ray angiography videos exclusively. First, we train a neural network model with angiographic sequences to extract features describing the progression of the cardiac cycle. Then, we compute the distance between the feature vectors of every frame from the first view with those from the second view to generate distance maps that display stripe patterns. Using pathfinding, we extract the best temporally coherent associations between each frame of both videos. Finally, we compare the synchronized frames of an evaluation set with the ECG signals to show an alignment with 96.04% accuracy

Statistical atlas-based descriptor for an early detection of optic disc abnormalities

Optic disc (OD) appearance in fundus images is one of the clinical indicators considered in the assessment of retinal diseases such as glaucoma. The cup-to-disc ratio (CDR) is the most common clinical measurement used to characterize glaucoma. However, the CDR only evaluates the relative sizes of the cup and the OD via their diameters. We propose to construct an atlas-based shape descriptor (ASD) to statistically characterize the geometric deformations of the OD shape and of the blood vessels' configuration inside the OD region. A local representation of the OD region is proposed to construct a well-defined statistical atlas using nonlinear registration and statistical analysis of deformation fields. The shape descriptor is defined as being composed of several statistical measures from the atlas. Analysis of the average model and its principal modes of deformation are performed on a healthy population. The components of the ASD show a significant difference between pathological and healthy ODs. We show that the ASD is able to characterize healthy and glaucomatous OD regions. The deviation map extracted from the atlas can be used to assist clinicians in an early detection of deformation abnormalities in the OD region

Meso-scale phytophysiognomic units in the Northern Pantanal and their relations with geomorphology

Este trabalho teve por objetivo caracterizar e quantificar as unidades fitofisionômicas em mesoescala e estabelecer suas relações com a intensidade e duração da inundação e com a topografia. O estudo foi realizado no Sítio de Amostragem de Longa Duração (SALD), implantado em uma área de 25 km2 localizado na planície de inundação do rio Cuiabá, Pantanal de Mato Grosso. As unidades fitofisionômicas foram determinadas a partir da classificação supervisionada de imagens CBERS 2B sensor CCD. Os mapas de intensidade e duração da inundação e topografia foram gerados a partir da interpolação espacial de levantamentos planialtimétricos de campos. Foi evidenciada a existência de quatro unidades, sendo o Campo (pastagem inundável) a unidade com maior área de ocorrência, seguido pelas Cordilheiras (savana arbórea densa), Landizal (floresta inundável sempre verde) e Cambarazal (floresta inundável monodominante de Vochysia divergens Pohl.) respectivamente. O Campo apresentou sua maior distribuição em áreas de alta intensidade e duração de inundação e topografia baixa. O Cambarazal predomina em áreas de intensidade média e duração e topografia alta, o Landizal em áreas com intensidade e duração alta e topografia baixa, enquanto as cordilheiras são caracterizadas por intensidade e duração baixa e topografia alta. Testes estatísticos indicaram que a inundação foi o principal fator responsável pela distribuição das unidades fitofisionômicas em mesoescala no Pantanal norte.The purpose of this work was to characterize and quantify phytophysiognomic units at mesoscale and evaluate their relationships with flood intensity, flood duration and topography. The study was conducted at a 25 km2 Long-Term Sampling Site (LTSS), located within the floodplain of the Cuiabá River in the Pantanal of Mato Grosso. The phytophysiognomic units were determined from the supervised classification of CBERS 2B sensor CCD satellite images. The maps of flood intensity, flood duration and of topography were generated from the spatial interpolation of planialtimetric field surveys. Four phytophysiognomic units were identified; Campo inundável (flooded grassland) was the unit with the largest area of occurrence, followed by Cordilheiras (dense arboreal savanna), Landizal (seasonally flooded evergreen forest), and Cambarazal (monodominant Vochysia divergens Pohl. forest), respectively. Campo inundável is distributed mainly in areas of high flood intensity and duration and low topographic positions. Cambarazal predominates in areas of medium flood intensity and duration and intermediate elevation, Landizal in areas of high flood intensity and duration and low topographic position, whereas Cordilheiras are characterized by low flood intensity and duration and location in higher elevations. Statistical tests indicated that flood intensity is the main factor responsible for the mesoscale distribution of phytophysiognomic units in the northern Pantanal

Caracterização morfométrica e suas implicações na limnologia de lagoas do Pantanal Norte - DOI: 10.4025/actascibiolsci.v30i2.3628

The objective of this work is to describe the morphological characteristics of seven Northern Pantanal lakes and discuss their implications on the limnology of these environments. The following morphological parameters were used: area; volume; maximum, mean and relative depths; perimeter; volume and perimeter development indices; maximum length and width. Generally, most lakes are shallow, with low relative depths, suggesting little thermal stratification, as they are more susceptible to mixing of the water column and suspended sediments by wind action. Most lakes have regular banks (few irregularities) and have a concave shape, and thus are less subject to erosion processes. Temporal variations in the morphometry of these lakes are related to the hydrodynamic and limnological patterns of these systems.O presente trabalho tem como objetivo descrever as características morfométricas de sete lagoas do Pantanal Norte e discutir suas implicações na limnologia deste ambientes. Os parâmetros utilizados foram: área, volume, profundidades máxima, média e relativa, perímetro, índices de desenvolvimento de volume e perímetro, comprimento e largura máxima. De modo geral, as maiorias das lagoas são rasas com pequenas profundidades relativas, assim menos propensas a estratificações térmicas e mais susceptíveis a ação dos ventos que atua como agente na resuspensão de matéria e mistura da coluna de água. Apresentam margens pouco irregulares e forma da bacia côncava que são menos influenciadas pelos processos de a erosão e sedimentação. Variações temporais na morfometria das lagoas conseqüentemente afetam os padrões hidrodinâmicos e limnológicos destes sistemas

Caracterização morfométrica e suas implicações na limnologia de lagoas do Pantanal Norte = Morphometric characterization and its limnological implications in Northern Pantanal lakes

O presente trabalho tem como objetivo descrever as característicasmorfométricas de sete lagoas do Pantanal Norte e discutir suas implicações na limnologia deste ambientes. Os parâmetros utilizados foram: área, volume, profundidades máxima, média e relativa, perímetro, índices de desenvolvimento de volume e perímetro,comprimento e largura máxima. De modo geral, as maiorias das lagoas são rasas com pequenas profundidades relativas, assim menos propensas a estratificações térmicas e mais susceptíveis a ação dos ventos que atua como agente na resuspensão de matéria e mistura da coluna de água. Apresentam margens pouco irregulares e forma da bacia côncava que são menos influenciadas pelos processos de a erosão e sedimentação. Variações temporais na morfometria das lagoas conseqüentemente afetam os padrões hidrodinâmicos e limnológicos destes sistemas.The objective of this work is to describe the morphologicalcharacteristics of seven Northern Pantanal lakes and discuss their implications on the limnology of these environments. The following morphological parameters were used: area; volume; maximum, mean and relative depths; perimeter; volume and perimeter development indices; maximum length and width. Generally, most lakes are shallow, withlow relative depths, suggesting little thermal stratification, as they are more susceptible to mixing of the water column and suspended sediments by wind action. Most lakes have regular banks (few irregularities) and have a concave shape, and thus are less subject toerosion processes. Temporal variations in the morphometry of these lakes are related to the hydrodynamic and limnological patterns of these systems