Adaptive morphological filters based on a multiple orientation vector field dependent on image local features

This paper addresses the formulation of adaptive morphological filters based on spatially-variant structuring elements. The adaptivity of these filters is achieved by modifying the shape and orientation of the structuring elements according to a multiple orientation vector field. This vector field is provided by means of a bank of directional openings which can take into account the possible multiple orientations of the contours in the image. After reviewing and formalizing the definition of the spatially-variant dilation, erosion, opening and closing, the proposed structuring elements are described. These spatially-variant structuring elements are based on ellipses which vary over the image domain adapting locally their orientation according to the multiple orientation vector field and their shape (the eccentricity of the ellipses) according to the distance to relevant contours of the objects. The proposed adaptive morphological filters are used on gray-level images and are compared with spatially-invariant filters, with spatially-variant filters based on a single orientation vector field, and with adaptive morphological bilateral filters. Results show that the morphological filters based on a multiple orientation vector field are more adept at enhancing and preserving structures which contains more than one orientation

3D mechanical characterization of artificial muscles with stereoscopic computer vision and active contours

Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. Applying an electrical current on the muscle. a macroscopic bending movement appears on it. Study of curvature variations and related parameters, such as speed of motion or energy of curvature, is necessary for improving the efficiency of these devices. In a previous work. a one-cam computer vision system was developed to estimate motion parameters in 2D with precise results. In this paper, a two-cam stereo vision system is proposed to process the image sequence and track the muscle in 3D. Active contours models are employed in motion detection and mechanical parameters estimation. Results prove the validity of this approach, allowing automatic testing on the research into artificial muscles.This work was supported by MCYI' BQLJ2001-047

Regularizador híbrido para el registro a medida de imágenes médicas

Durante los últimos dos años, ha surgido un gran interés por encontrar nuevos términos de regularización que resulten especialmente adecuados para el registro de imágenes médicas. Los ejemplos más recientes en la literatura están basados en derivadas de primer y/o segundo orden. En este trabajo se propone un nuevo regularizador, basado en derivadas de orden fraccionario, para el registro de imágenes médicas. Puede considerarse como una generalización de los métodos de registro por difusión (derivadas de primer orden) y por curvatura (derivadas de segundo orden), pero con la estrategia propuesta es posible obtener mejores resultados en el registro final desde el punto de vista variacional (i.e., en términos tanto de similitud entre las imágenes como de suavidad en la transformación estimada), y en un menor número de iteraciones del algoritmo de registro.Ministerio de Ciencia y Tecnología a través del proyecto TEC2006-13338/TCM, y por la Agencia Regional de Ciencia y Tecnología (Fundación Séneca) a través del proyecto 03122/PI/05

Determination of bifurcation angles of the retinal vascular tree through multiple orientation estimation based on regularized morphological openings

This paper describes a new approach to compute bifurcation angles in retinal images. This approach is based on the estimation of multiple orientations at each pixel of a gray retinal image. The main orientations are provided by directional openings whose outputs are regularized in order to extend the orientation information to the whole image. The detection of vessel bifurcations is based on the coexistence of two or more than two different main orientations at the same pixel. Once the bifurcations and crossovers has been identified, bifurcation angles are calculated. The proposed procedure of computing bifurcation angles by means of orientation estimation at all pixels of the gray level image is much more stable than those methods which are based on the skeleton of the vascular tree, since a slight variation of a pixel of the skeleton can produce a significant change in the angle valueThis work was supported by Ministerio de Economía y Competitividad of Spain,Project ACRIMA (TIN2013-46751-R)

Multiple feature models for image matching

The common approach to image matching is to detect spatial features present in both images and create a mapping that relates both images. The main draw back of this method takes place when more than one matching is likely. A first simplification to this ambiguity is to represent with apara-metric model the point locus where the matching is highly likely,and then use a POCS(projection on to convex sets)procedure combined with Tikhonov regularization that results in the mapping vectors. However,if there is more than one model perpixel,the regularization and constrainforcing process faces a multiplechoice dilemma that has no easy solution. This work proposes a frame work to overcome this draw back: the combined projection over multiple models base don the norm of the projection–pointdis-tance. This approach is tested on a stereo-pair that presents multiple choices of similar likelihood.This work is partially supported by the Spanish Ministerio de Ciencia y Tecnología,under grant TIC2002-03033

Registro variacional óptimo de imágenes médicas

La correcta selección de parámetros en los métodos de registro no paramétrico de imagen es un problema aún sin resolver. No hay acuerdo sobre cuáles son valores óptimos de estos parámetros, que dependen de las propias imágenes a registrar. Para abordar este problema, en este trabajo se propone un método que consta de dos pasos para obtener los parámetros que nos ofrecen desde un punto de vista variacional el compromiso óptimo entre la similitud de las imágenes registradas y la suavidad de la transformación resultante

A Self-Training Framework for Glaucoma Grading In OCT B-Scans

[EN] In this paper, we present a self-training-based framework for glaucoma grading using OCT B-scans under the presence of domain shift. Particularly, the proposed two-step learning methodology resorts to pseudo-labels generated during the first step to augment the training dataset on the target domain, which is then used to train the final target model. This allows transferring knowledge-domain from the unlabeled data. Additionally, we propose a novel glaucoma-specific backbone which introduces residual and attention modules via skip-connections to refine the embedding features of the latent space. By doing this, our model is capable of improving state-of-the-art from a quantitative and interpretability perspective. The reported results demonstrate that the proposed learning strategy can boost the performance of the model on the target dataset without incurring in additional annotation steps, by using only labels from the source examples. Our model consistently outperforms the baseline by 1¿3% across different metrics and bridges the gap with respect to training the model on the labeled target data.We gratefully acknowledge the support of the Generalitat Valenciana (GVA) for the donation of the DGX A100 used for this work, action co-financed by the European Union through the Programa Operativo del Fondo Europeo de Desarrollo Regional (FEDER) de la Comunitat Valenciana 2014-2020 (IDIFEDER/2020/030).García-Pardo, JG.; Colomer, A.; Verdú-Monedero, R.; Dolz, J.; Naranjo Ornedo, V. (2021). A Self-Training Framework for Glaucoma Grading In OCT B-Scans. IEEE. 1281-1285. https://doi.org/10.23919/EUSIPCO54536.2021.9616159S1281128

Estimación de parámetros de músculos artificiales usando contornos activos y visión estereoscópica

Conducting polymers have the ability to transform electrical energy into mechanical energy through an electrochemical reaction. Artificial muscles are formed by attaching a conducting polymeric film to a non-conducting one. Applying an electrical current on the muscle, a bending movement appears on it. A one-cam computer vision system has performed this study of electromechanical properties using active contour models. This system shows the movement only in the normal direction of the camera. In this paper we propose a preliminary two-cam stereovision system to study these properties in 3D

Medida de similitud mixta para el registro y fusión de imágenes

En este trabajo se presenta un método de registro y fusión de imágenes que hace uso de una medida de similitud mixta, basada en la correlación cruzada normalizada y la diferencia cuadrática media. Históricamente se han utilizado muchas medidas de similitud, pero ninguna es válida para cualquier tipo de imágenes. El uso de medidas de similitud combinadas permite conjugar las propiedades de detección de patrones de diversas medidas de similitud en una sola medida. La medida combinada de similitud propuesta se puede utilizar para registro multimodal de imágenes médicas. Para este propósito, el algoritmo presentado calcula primero la relación entre las intensidades de píxel de cada imagen, partiendo del histograma conjunto de niveles de gris. Entonces se aplica el método de estimación de movimiento no rígido basado en modelos difusos. Los resultados de registro multimodal y fusión de imágenes de CT con PET mostrados prueban la validez del método propuesto.Este trabajo ha sido financiado por el Ministerio de Ciencia y Tecnología a través del proyecto TIC2002-0303

Estimación iterativa de moviemiento no rígido basada en modelos paramétricos

La correspondencia entre estructuras deformables ha atraído gran atención en los últimos tiempos dentro del procesado de imagen y sobre todo en el campo médico. Este trabajo propone un método que aborda el problema que por naturaleza se encuentra mal condicionado utilizando una función de coste de similitud de reducido tamaño: la ambigüedad en cada mapa de similitud se describe mediante un modelo paramétrico difuso, y finalmente se lleva a cabo una interpolación difusa y espacialmente no uniforme, para transformar la información paramétrica en un conjunto de vectores de movimiento. El método obtiene la correspondencia espacial entre dos imágenes de forma global y con precisión subpixel. Los resultados del método en imágenes reales con alta deformación no lineal prueban la validez de este método. La extensión al caso volumétrico es también posibl