Enhanced algorithms for lesion detection and recognition in ultrasound breast images

Mammography is the gold standard for breast cancer detection. However, it has very high false positive rates and is based on ionizing radiation. This has led to interest in using multi-modal approaches. One modality is diagnostic ultrasound, which is based on non-ionizing radiation and picks up many of the cancers that are generally missed by mammography. However, the presence of speckle noise in ultrasound images has a negative effect on image interpretation. Noise reduction, inconsistencies in capture and segmentation of lesions still remain challenging open research problems in ultrasound images. The target of the proposed research is to enhance the state-of-art computer vision algorithms used in ultrasound imaging and to investigate the role of computer processed images in human diagnostic performance. [Continues.

Doctor of Philosophy

dissertationCongenital heart defects are classes of birth defects that affect the structure and function of the heart. These defects are attributed to the abnormal or incomplete development of a fetal heart during the first few weeks following conception. The overall detection rate of congenital heart defects during routine prenatal examination is low. This is attributed to the insufficient number of trained personnel in many local health centers where many cases of congenital heart defects go undetected. This dissertation presents a system to identify congenital heart defects to improve pregnancy outcomes and increase their detection rates. The system was developed and its performance assessed in identifying the presence of ventricular defects (congenital heart defects that affect the size of the ventricles) using four-dimensional fetal chocardiographic images. The designed system consists of three components: 1) a fetal heart location estimation component, 2) a fetal heart chamber segmentation component, and 3) a detection component that detects congenital heart defects from the segmented chambers. The location estimation component is used to isolate a fetal heart in any four-dimensional fetal echocardiographic image. It uses a hybrid region of interest extraction method that is robust to speckle noise degradation inherent in all ultrasound images. The location estimation method's performance was analyzed on 130 four-dimensional fetal echocardiographic images by comparison with manually identified fetal heart region of interest. The location estimation method showed good agreement with the manually identified standard using four quantitative indexes: Jaccard index, Sørenson-Dice index, Sensitivity index and Specificity index. The average values of these indexes were measured at 80.70%, 89.19%, 91.04%, and 99.17%, respectively. The fetal heart chamber segmentation component uses velocity vector field estimates computed on frames contained in a four-dimensional image to identify the fetal heart chambers. The velocity vector fields are computed using a histogram-based optical flow technique which is formulated on local image characteristics to reduces the effect of speckle noise and nonuniform echogenicity on the velocity vector field estimates. Features based on the velocity vector field estimates, voxel brightness/intensity values, and voxel Cartesian coordinate positions were extracted and used with kernel k-means algorithm to identify the individual chambers. The segmentation method's performance was evaluated on 130 images from 31 patients by comparing the segmentation results with manually identified fetal heart chambers. Evaluation was based on the Sørenson-Dice index, the absolute volume difference and the Hausdorff distance, with each resulting in per patient average values of 69.92%, 22.08%, and 2.82 mm, respectively. The detection component uses the volumes of the identified fetal heart chambers to flag the possible occurrence of hypoplastic left heart syndrome, a type of congenital heart defect. An empirical volume threshold defined on the relative ratio of adjacent fetal heart chamber volumes obtained manually is used in the detection process. The performance of the detection procedure was assessed by comparison with a set of images with confirmed diagnosis of hypoplastic left heart syndrome and a control group of normal fetal hearts. Of the 130 images considered 18 of 20 (90%) fetal hearts were correctly detected as having hypoplastic left heart syndrome and 84 of 110 (76.36%) fetal hearts were correctly detected as normal in the control group. The results show that the detection system performs better than the overall detection rate for congenital heart defect which is reported to be between 30% and 60%

Generalised morphological image diffusion

International audienceRelationships between linear and morphological scale-spaces have been considered by various previous works. The aim of this paper is to study how to generalise the diffusion-based approaches in order to introduce nonlinear filters whose effects mimic the asymmetric behaviour of morphological dilation and erosion, as well as other evolved morphological filters. A methodology based on the counter-harmonic mean is adopted here. Details of numerical implementation are discussed and results are provided to illustrate the various studied cases: isotropic, nonlinear and coherence-enhancing diffusion. We also found a new way to derive the classical link between Gaussian scale-space and dilation/erosion scale-spaces based on quadratic structuring functions. We have included some preliminary applications of the generalised morphological diffusion to solve image processing problems such as denoising and image enhancement in the case of asymmetric bright/dark image properties

Filtrage anisotrope robuste et segmentation par B-spline snake : application aux images échographiques

Le contexte de ce travail est le traitement d'images échographiques. Plus précisément, on s'est intéressé au filtrage et à la segmentation automatique d'images dégradées par du speckle. La première partie concerne les travaux effectués sur le filtrage du speckle. Ils ont abouti à la conception d'une méthode de diffusion anisotrope robuste, nommée -diffusion. Elle se fonde sur un coefficient de diffusion original qui exploite lui-mˆeme la statistique du coefficient de variation et une adaptation de la fonction de Tukey. Un estimateur robuste du paramètre d'échelle de ce filtre est présenté. L'évolution de la diffusion est modélisée par une équation aux dérivées partielles s'appliquant sur l'enveloppe du signal brut, non compressée logarithmiquement. Cette approche permet de réduire le bruit des images échographiques, tout en préservant les structures importantes pour leur interprétation. Dans la deuxieme partie, nous présentons un contour actif paramétrique de type B-spline snake. L'étude de la continuité géométrique des B-splines nous permet de justifier le choix de l'énergie interne. Nous proposons deux nouvelles énergies externes qui exploitent notamment un champ de flux de vecteurs gradients, nommé s-GVF, calculé sur une carte de coefficients de variation locaux. Une fonction d'inhibition contrôle l'influence respective de ces deux énergies externe lors de l'évolution du snake. Enfin, nous proposons une nouvelle méthode d'initialisation automatique pour contour actif paramétrique. Une application au cas du filtrage des images echographiques et de la segmentation des cavités cardiaques est présentée. Les résultats démontrent une robustesse et une précision accrue par les modèles proposés par rapport aux techniques classiques de filtrage et segmentation par contours actifs. ABSTRACT : This thesis presents a robust model for speckle anisotropic filtering, and a parametric active contour model (B-spline snake) for the segmentation of images affected by speckle. First an original diffusion tensor is developed. It is based on the Tukey's error norm and on a local estimation of the coefficient of variation. The diffusion evolution is modelled by a partial derivative equation for raw images with no log-compression. This model reduces speckle while preserving important image features that are used by doctors to perform a diagnosis. Then we present a B-spline snake model with an external energy term that uses the amplitude and direction of the coefficient of variation gradient. The geometric continuity is guaranted by a uniform parametrisation and an internal energy term which penalizes the curve for irregular nodes spacing. An application to ultrasound image filtering and heart cavities detection is presented

Contributions à la segmentation d'image : phase locale et modèles statistiques

Ce document presente une synthèse de mes travaux apres these, principalement sur la problematique de la segmentation d’images

Digital Image Processing Applications

Digital image processing can refer to a wide variety of techniques, concepts, and applications of different types of processing for different purposes. This book provides examples of digital image processing applications and presents recent research on processing concepts and techniques. Chapters cover such topics as image processing in medical physics, binarization, video processing, and more

Automated retinal layer segmentation and pre-apoptotic monitoring for three-dimensional optical coherence tomography

The aim of this PhD thesis was to develop segmentation algorithm adapted and optimized to retinal OCT data that will provide objective 3D layer thickness which might be used to improve diagnosis and monitoring of retinal pathologies. Additionally, a 3D stack registration method was produced by modifying an existing algorithm. A related project was to develop a pre-apoptotic retinal monitoring based on the changes in texture parameters of the OCT scans in order to enable treatment before the changes become irreversible; apoptosis refers to the programmed cell death that can occur in retinal tissue and lead to blindness. These issues can be critical for the examination of tissues within the central nervous system. A novel statistical model for segmentation has been created and successfully applied to a large data set. A broad range of future research possibilities into advanced pathologies has been created by the results obtained. A separate model has been created for choroid segmentation located deep in retina, as the appearance of choroid is very different from the top retinal layers. Choroid thickness and structure is an important index of various pathologies (diabetes etc.). As part of the pre-apoptotic monitoring project it was shown that an increase in proportion of apoptotic cells in vitro can be accurately quantified. Moreover, the data obtained indicates a similar increase in neuronal scatter in retinal explants following axotomy (removal of retinas from the eye), suggesting that UHR-OCT can be a novel non-invasive technique for the in vivo assessment of neuronal health. Additionally, an independent project within the computer science department in collaboration with the school of psychology has been successfully carried out, improving analysis of facial dynamics and behaviour transfer between individuals. Also, important improvements to a general signal processing algorithm, dynamic time warping (DTW), have been made, allowing potential application in a broad signal processing field.EThOS - Electronic Theses Online ServiceGBUnited Kingdo

Automated retinal layer segmentation and pre-apoptotic monitoring for three-dimensional optical coherence tomography

The aim of this PhD thesis was to develop segmentation algorithm adapted and optimized to retinal OCT data that will provide objective 3D layer thickness which might be used to improve diagnosis and monitoring of retinal pathologies. Additionally, a 3D stack registration method was produced by modifying an existing algorithm. A related project was to develop a pre-apoptotic retinal monitoring based on the changes in texture parameters of the OCT scans in order to enable treatment before the changes become irreversible; apoptosis refers to the programmed cell death that can occur in retinal tissue and lead to blindness. These issues can be critical for the examination of tissues within the central nervous system. A novel statistical model for segmentation has been created and successfully applied to a large data set. A broad range of future research possibilities into advanced pathologies has been created by the results obtained. A separate model has been created for choroid segmentation located deep in retina, as the appearance of choroid is very different from the top retinal layers. Choroid thickness and structure is an important index of various pathologies (diabetes etc.). As part of the pre-apoptotic monitoring project it was shown that an increase in proportion of apoptotic cells in vitro can be accurately quantified. Moreover, the data obtained indicates a similar increase in neuronal scatter in retinal explants following axotomy (removal of retinas from the eye), suggesting that UHR-OCT can be a novel non-invasive technique for the in vivo assessment of neuronal health. Additionally, an independent project within the computer science department in collaboration with the school of psychology has been successfully carried out, improving analysis of facial dynamics and behaviour transfer between individuals. Also, important improvements to a general signal processing algorithm, dynamic time warping (DTW), have been made, allowing potential application in a broad signal processing field