Histopathological image analysis : a review

Over the past decade, dramatic increases in computational power and improvement in image analysis algorithms have allowed the development of powerful computer-assisted analytical approaches to radiological data. With the recent advent of whole slide digital scanners, tissue histopathology slides can now be digitized and stored in digital image form. Consequently, digitized tissue histopathology has now become amenable to the application of computerized image analysis and machine learning techniques. Analogous to the role of computer-assisted diagnosis (CAD) algorithms in medical imaging to complement the opinion of a radiologist, CAD algorithms have begun to be developed for disease detection, diagnosis, and prognosis prediction to complement the opinion of the pathologist. In this paper, we review the recent state of the art CAD technology for digitized histopathology. This paper also briefly describes the development and application of novel image analysis technology for a few specific histopathology related problems being pursued in the United States and Europe

Introduction to fMRI: experimental design and data analysis

This provides an introduction to functional MRI, experimental design and data analysis procedures using statistical parametric mapping approach

Mesh-based video coding for low bit-rate communications

In this paper, a new method for low bit-rate content-adaptive mesh-based video coding is proposed. Intra-frame coding of this method employs feature map extraction for node distribution at specific threshold levels to achieve higher density placement of initial nodes for regions that contain high frequency features and conversely sparse placement of initial nodes for smooth regions. Insignificant nodes are largely removed using a subsequent node elimination scheme. The Hilbert scan is then applied before quantization and entropy coding to reduce amount of transmitted information. For moving images, both node position and color parameters of only a subset of nodes may change from frame to frame. It is sufficient to transmit only these changed parameters. The proposed method is well-suited for video coding at very low bit rates, as processing results demonstrate that it provides good subjective and objective image quality at a lower number of required bits

Focal Spot, Spring 2000

https://digitalcommons.wustl.edu/focal_spot_archives/1084/thumbnail.jp

Digital Color Imaging

This paper surveys current technology and research in the area of digital color imaging. In order to establish the background and lay down terminology, fundamental concepts of color perception and measurement are first presented us-ing vector-space notation and terminology. Present-day color recording and reproduction systems are reviewed along with the common mathematical models used for representing these devices. Algorithms for processing color images for display and communication are surveyed, and a forecast of research trends is attempted. An extensive bibliography is provided

A study and evaluation of image analysis techniques applied to remotely sensed data

An analysis of phenomena causing nonlinearities in the transformation from Landsat multispectral scanner coordinates to ground coordinates is presented. Experimental results comparing rms errors at ground control points indicated a slight improvement when a nonlinear (8-parameter) transformation was used instead of an affine (6-parameter) transformation. Using a preliminary ground truth map of a test site in Alabama covering the Mobile Bay area and six Landsat images of the same scene, several classification methods were assessed. A methodology was developed for automatic change detection using classification/cluster maps. A coding scheme was employed for generation of change depiction maps indicating specific types of changes. Inter- and intraseasonal data of the Mobile Bay test area were compared to illustrate the method. A beginning was made in the study of data compression by applying a Karhunen-Loeve transform technique to a small section of the test data set. The second part of the report provides a formal documentation of the several programs developed for the analysis and assessments presented

A personal identification biometric system based on back-of-hand vein patterns

This report describes research on the use of back-of-hand vein patterns as a means of uniquely identifying people. In particular it describes a prototype biometric system developed by the Australian Institute of Security and Applied Technology (AISAT). This system comprises an infrared cold source, a monochrome CCD camera, a monochrome frame-grabber, a personal computer, and custom image acquisition, processing, registration, and matching software. The image processing algorithms are based on Mathematical Morphology. Registration is performed using rotation and translation with respect to the centroid of the two-dimensional domain of a hand. Vein patterns are stored as medial axis representations. Matching involves comparing a given medial axis pattern against a library of patterns using constrained sequential correlation. The matching is two-fold: a newly acquired signature is matched against a dilated library signature, and then the library signature is matched against the dilated acquired signature; this is necessary because of the positional noise exhibited by the back-of-hand veins. The results of a cross-matching experiment for a sample of 20 adults and more than 100 hand images is detailed. In addition preliminary estimates of the false acceptance rate (FAR) and false rejection rate (FRR) for the prototype system are given. Fuzzy relaxation on an association graph is discussed as an alternative to sequential correlation for the matching of vein signatures. An example is provided (including a C program) illustrating the matching process for a pair of signatures obtained from the same hand. The example demonstrates the ability of the fuzzy relaxation method to deal with segmentation errors

Doctor of Philosophy

dissertationNeuroscientists are developing new imaging techniques and generating large volumes of data in an effort to understand the complex structure of the nervous system. The complexity and size of this data makes human interpretation a labor intensive task. To aid in the analysis, new segmentation techniques for identifying neurons in these feature rich datasets are required. However, the extremely anisotropic resolution of the data makes segmentation and tracking across slices difficult. Furthermore, the thickness of the slices can make the membranes of the neurons hard to identify. Similarly, structures can change significantly from one section to the next due to slice thickness which makes tracking difficult. This thesis presents a complete method for segmenting many neurons at once in two-dimensional (2D) electron microscopy images and reconstructing and visualizing them in three-dimensions (3D). First, we present an advanced method for identifying neuron membranes in 2D, necessary for whole neuron segmentation, using a machine learning approach. The method described uses a series of artificial neural networks (ANNs) in a framework combined with a feature vector that is composed of image and context; intensities sampled over a stencil neighborhood. Several ANNs are applied in series allowing each ANN to use the classification context; provided by the previous network to improve detection accuracy. To improve the membrane detection, we use information from a nonlinear alignment of sequential learned membrane images in a final ANN that improves membrane detection in each section. The final output, the detected membranes, are used to obtain 2D segmentations of all the neurons in an image. We also present a method that constructs 3D neuron representations by formulating the problem of finding paths through sets of sections as an optimal path computation, which applies a cost function to the identification of a cell from one section to the next and solves this optimization problem using Dijkstras algorithm. This basic formulation accounts for variability or inconsistencies between sections and prioritizes cells based on the evidence of their connectivity. Finally, we present a tool that combines these techniques with a visual user interface that enables users to quickly segment whole neurons in large volumes

Mosaicing Tool for Aerial Imagery from a Lidar Bathymetry Survey

Aerial imagery collected during lidar bathymetry surveying provides an independent reference dataset for ground truth. Mosaicing of aerial imagery requires some manual involvement by the operator, which is time consuming. This paper presents an automatic mosaicing procedure that creates a continuous and visually consistent photographic map of the imaged area. This study aimed to use only the frames from the aerial camera without additional information. A comparison between the features in the resultant mosaic and a reference chart shows that the mosaic is visually consistent and there is good spatial-geometric correlation of features.Las imagenes aereas recogidas durante los levantamientos batimetricos efectuados con el lfdar proporcionan una coleccion de datos de referencia independientes para la validacion en el terreno. La composicion de las imagenes aereas en forma de mosaico requiere una cierta implicacion manual par parte del operador, to que toma mucho tiempo. Este articulo presenta un procedimiento para la composicion automatica en forma de mosaico, que crea un mapa fotografico continuo y visuatmente coherente de la zona representada en la imagen. El objetivo de este estudio es utilizar solo los marcos de la camara aerea sin informacion adicional. Una comparacion entre las caracterfsticas del mosaico resultante y una carta de referencia muestra que el mosaico es visualmente coherente y que hay una buena correlacion geometrico-espacial de las caracteristicas.L'imagerie aerienne effectuee pendant les leves bathymetriques lidar constitue un ensemble de donnees de reference independant, pour la realite de terrain. Le mosaiiquage de l'imagerie aerienne requiert une intervention manuelle de l'operateur, laquelle prend beaucoup de temps. Cet article presente une procedure de mosaiiquage automatique qui permet d'obtenir une carte photographique continue et visuellement coherente de la zone couverte. L'objectif de cette etude consiste a utiliser seulement les images de la camera aerienne sans informations supptementaires. Une comparaison entre tes elements dans la mosaique resultante et une carte de reference montre que la mosaique est visuellement coherente et qu'il existe une bonne correlation geometrique-spatiale des elements

Mosaicing Tool for Aerial Imagery from a Lidar Bathymetry Survey

Aerial imagery collected during lidar bathymetry surveying provides an independent reference dataset for ground truth. Mosaicing of aerial imagery requires some manual involvement by the operator, which is time consuming. This paper presents an automatic mosaicing procedure that creates a continuous and visually consistent photographic map of the imaged area. This study aimed to use only the frames from the aerial camera without additional information. A comparison between the features in the resultant mosaic and a reference chart shows that the mosaic is visually consistent and there is good spatial-geometric correlation of features.Las imagenes aereas recogidas durante los levantamientos batimetricos efectuados con el lfdar proporcionan una coleccion de datos de referencia independientes para la validacion en el terreno. La composicion de las imagenes aereas en forma de mosaico requiere una cierta implicacion manual par parte del operador, to que toma mucho tiempo. Este articulo presenta un procedimiento para la composicion automatica en forma de mosaico, que crea un mapa fotografico continuo y visuatmente coherente de la zona representada en la imagen. El objetivo de este estudio es utilizar solo los marcos de la camara aerea sin informacion adicional. Una comparacion entre las caracterfsticas del mosaico resultante y una carta de referencia muestra que el mosaico es visualmente coherente y que hay una buena correlacion geometrico-espacial de las caracteristicas.L'imagerie aerienne effectuee pendant les leves bathymetriques lidar constitue un ensemble de donnees de reference independant, pour la realite de terrain. Le mosaiiquage de l'imagerie aerienne requiert une intervention manuelle de l'operateur, laquelle prend beaucoup de temps. Cet article presente une procedure de mosaiiquage automatique qui permet d'obtenir une carte photographique continue et visuellement coherente de la zone couverte. L'objectif de cette etude consiste a utiliser seulement les images de la camera aerienne sans informations supptementaires. Une comparaison entre tes elements dans la mosaique resultante et une carte de reference montre que la mosaique est visuellement coherente et qu'il existe une bonne correlation geometrique-spatiale des elements