Interactive volume exploration for feature detection and quantification in industrial CT data.

This paper presents a novel method for interactive exploration of industrial CT volumes such as cast metal parts, with the goal of interactively detecting, classifying, and quantifying features using a visualization-driven approach. The standard approach for defect detection builds on region growing, which requires manually tuning parameters such as target ranges for density and size, variance, as well as the specification of seed points. If the results are not satisfactory, region growing must be performed again with different parameters.

Interactive visual analysis of set-typed data.

While it is quite typical to deal with attributes of different data types in the visualization of heterogeneous and multivariate datasets, most existing techniques still focus on the most usual data types such as numerical attributes or strings. In this paper we present a new approach to the interactive visual exploration and analysis of data that contains attributes which are of set type. A set-typed attribute of a data item--like one cell in a table--has a list of n > or = 0 elements as its value.

Entropy-optimized texture models.

In order to robustly match a statistical model of shape and appearance (e.g. AAM) to an unseen image, it is crucial to employ a robust model fittness measure.

High-quality multimodal volume rendering for preoperative planning of neurosurgical interventions.

Surgical approaches tailored to an individual patient's anatomy and pathology have become standard in neurosurgery. Precise preoperative planning of these procedures, however, is necessary to achieve an optimal therapeutic effect. Therefore, multiple radiological imaging modalities are used prior to surgery to delineate the patient's anatomy, neurological function, and metabolic processes.

Scalable hybrid unstructured and structured grid raycasting.

This paper presents a scalable framework for real-time raycasting of large unstructured volumes that employs a hybrid bricking approach. It adaptively combines original unstructured bricks in important (focus) regions, with structured bricks that are resampled on demand in less important (context) regions. The basis of this focus+context approach is interactive specification of a scalar degree of interest (DOI) function.

Interactive diffusion-based smoothing and segmentation of volumetric datasets on graphics hardware.

Objective: Volume segmentation with concurrent visualization is becoming an increasingly important part of medical diagnostics. This is due to the fact that the immediate visual feedback speeds up evaluation of the segmentation process, hence enhances segmentation quality. Therefore, our aim was to develop a method for volume segmentation and smoothing which achieves interactive performance on standard PCs and is useful in clinical practice (i.

Improving segmentation of the left ventricle using a two-component statistical model.

Quality of segmentations obtained by 3D Active Appearance Models (AAMs) crucially depends on underlying training data. MRI heart data, however, often come noisy, incomplete, with respiratory-induced motion, and do not fulfill necessary requirements for building an AAM. Moreover, AAMs are known to fail when attempting to model local variations.

Interactive visual analysis of families of function graphs.

The analysis and exploration of multidimensional and multivariate data is still one of the most challenging areas in the field of visualization. In this paper, we describe an approach to visual analysis of an especially challenging set of problems that exhibit a complex internal data structure. We describe the interactive visual exploration and analysis of data that includes several (usually large) families of function graphs fi (x, t).

Advanced virtual endoscopic pituitary surgery.

Endoscopy has recently been introduced to endonasal transsphenoidal pituitary surgery as a minimally invasive procedure for the removal of various kinds of pituitary tumors. To reduce morbidity and mortality with this new technique, the surgeon must be well-trained and well-prepared. Virtual endoscopy can be beneficial as a tool for training, preoperative planning, and intraoperative support.

ISA and IBFVS: image space-based visualization of flow on surfaces.

We present a side-by-side analysis of two recent image space approaches for the visualization of vector fields on surfaces. The two methods, Image Space Advection (ISA) and Image-Based Flow Visualization for Curved Surfaces (IBFVS) generate dense representations of time-dependent vector fields with high spatio-temporal correlation. While the 3D vector fields are associated with arbitrary surfaces represented by triangular meshes, the generation and advection of texture properties is confined to image space.

Visualization methods for data analysis and planning in medical applications.

Time plays an important role in medicine, both the past and the future. The medical history of a patient represents the past, which needs to be understood by the physician to make the right decisions. The past contains two different kinds of information: measured data (such as blood pressure) and incidents (such as seizures).