Adaptive transfer functions

García, Jesús Díaz; Brunet, Pere; Navazo, Isabel; Pérez, Frederic; Vázquez, Pere‐Pau

doi:10.1007/s00371-016-1253-9

Cited by 3 publications

(3 citation statements)

References 25 publications

(27 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In Chapter 4 we present an evaluation of different downsampling filters used to generate coarser representations of the original dataset, and we analyze their effectiveness at preserving details. Moreover, we propose a new Gaussian-based, feature-preserving filter that produces quality low-resolution representations and conserves small features that are prone to disappear during the downsampling process [15,17].…”

Section: Addressed Problems and Contributionsmentioning

confidence: 99%

“…In particular, the Transfer Function originally designed for the original scalar field might be not valid anymore for coarser representations. In Chapter 6, we present Adaptive Transfer Functions [16], an algorithm that, by modifying the original Transfer Function, generates custom Transfer Functions for downsampled models so that the quality of renderings is highly improved. The technique is simple and lightweight, and it is suitable not only to visualize huge models that would not fit in a GPU, but also to render not-so-large models in mobile GPUs, which are less capable than their desktop counterparts.…”

Section: Addressed Problems and Contributionsmentioning

confidence: 99%

“…In Chapter 4 we propose an alternative solution for downsampling scalar data. We present a downsampling filter [15,17] designed to preserve features typically lost during the generation of coarse representations of volume datasets, and still obtaining smooth results. The presented method takes just a few minutes to generate a downsampled version from any of the high-resolution datasets we used.…”

Section: Downsampling Of Scalar Datamentioning

confidence: 99%

See 2 more Smart Citations

Real-time quality visualization of medical models on commodity and mobile devices

Díaz García

View full text Add to dashboard Cite

This thesis concerns the specific field of visualization of medical models using commodity and mobile devices. Mechanisms for medical imaging acquisition such as MRI, CT, and micro-CT scanners are continuously evolving, up to the point of obtaining volume datasets of large resolutions (> 512^3). As these datasets grow in resolution, its treatment and visualization become more and more expensive due to their computational requirements. For this reason, special techniques such as data pre-processing (filtering, construction of multi-resolution structures, etc.) and sophisticated algorithms have to be introduced in different points of the visualization pipeline to achieve the best visual quality without compromising performance times. The problem of managing big datasets comes from the fact that we have limited computational resources. Not long ago, the only physicians that were rendering volumes were radiologists. Nowadays, the outcome of diagnosis is the data itself, and medical doctors need to render them in commodity PCs (even patients may want to render the data, and the DVDs are commonly accompanied with a DICOM viewer software). Furthermore, with the increasing use of technology in daily clinical tasks, small devices such as mobile phones and tablets can fit the needs of medical doctors in some specific areas. Visualizing diagnosis images of patients becomes more challenging when it comes to using these devices instead of desktop computers, as they generally have more restrictive hardware specifications. The goal of this Ph.D. thesis is the real-time, quality visualization of medium to large medical volume datasets (resolutions >= 512^3 voxels) on mobile phones and commodity devices. To address this problem, we use multiresolution techniques that apply downsampling techniques on the full resolution datasets to produce coarser representations which are easier to handle. We have focused our efforts on the application of Volume Visualization in the clinical practice, so we have a particular interest in creating solutions that require short pre-processing times that quickly provide the specialists with the data outcome, maximize the preservation of features and the visual quality of the final images, achieve high frame rates that allow interactive visualizations, and make efficient use of the computational resources. The contributions achieved during this thesis comprise improvements in several stages of the visualization pipeline. The techniques we propose are located in the stages of multi-resolution generation, transfer function design and the GPU ray casting algorithm itself. Esta tesis se centra en la visualización de modelos médicos de volumen en dispositivos móviles y de bajas prestaciones. Los sistemas médicos de captación tales como escáners MRI, CT y micro-CT, están en constante evolución, hasta el punto de obtener modelos de volumen de gran resolución (> 512^3). A medida que estos datos crecen en resolución, su manejo y visualización se vuelve más y más costoso debido a sus requisitos computacionales. Por este motivo, técnicas especiales como el pre-proceso de datos (filtrado, construcción de estructuras multiresolución, etc.) y algoritmos específicos se tienen que introducir en diferentes puntos de la pipeline de visualización para conseguir la mejor calidad visual posible sin comprometer el rendimiento. El problema que supone manejar grandes volumenes de datos es debido a que tenemos recursos computacionales limitados. Hace no mucho, las únicas personas en el ámbito médico que visualizaban datos de volumen eran los radiólogos. Hoy en día, el resultado de la diagnosis son los datos en sí, y los médicos necesitan renderizar estos datos en PCs de características modestas (incluso los pacientes pueden querer visualizar estos datos, pues los DVDs con los resultados suelen venir acompañados de un visor de imágenes DICOM). Además, con el reciente aumento del uso de las tecnologías en la clínica práctica habitual, dispositivos pequeños como teléfonos móviles o tablets son los más convenientes en algunos casos. La visualización de volumen es más difícil en este tipo de dispositivos que en equipos de sobremesa, pues las limitaciones de su hardware son superiores. El objetivo de esta tesis doctoral es la visualización de calidad en tiempo real de modelos grandes de volumen (resoluciones >= 512^3 voxels) en teléfonos móviles y dispositivos de bajas prestaciones. Para enfrentarnos a este problema, utilizamos técnicas multiresolución que aplican técnicas de reducción de datos a los modelos en resolución original, para así obtener modelos de menor resolución. Hemos centrado nuestros esfuerzos en la aplicación de la visualización de volumen en la práctica clínica, así que tenemos especial interés en diseñar soluciones que requieran cortos tiempos de pre-proceso para que los especialistas tengan rápidamente los resultados a su disposición. También, queremos maximizar la conservación de detalles de interés y la calidad de las imágenes finales, conseguir frame rates altos que faciliten visualizaciones interactivas y que hagan un uso eficiente de los recursos computacionales. Las contribuciones aportadas por esta tesis són mejoras en varias etapas de la pipeline de visualización. Las técnicas que proponemos se situan en las etapas de generación de la estructura multiresolución, el diseño de la función de transferencia y el algoritmo de ray casting en la GPU.

show abstract

Section: Addressed Problems and Contributionsmentioning

confidence: 99%

Section: Addressed Problems and Contributionsmentioning

confidence: 99%

Section: Downsampling Of Scalar Datamentioning

confidence: 99%

See 1 more Smart Citation

Real-time quality visualization of medical models on commodity and mobile devices

Díaz García

View full text Add to dashboard Cite

show abstract

CGI 2016 Editorial (TVCJ)

2016

View full text Add to dashboard Cite

Progressive ray casting for volumetric models on mobile devices

García

Brunet

Navazo

et al. 2018

Computers & Graphics

View full text Add to dashboard Cite

Mobile devices have experienced an incredible market penetration in the last decade. Currently, medium to premium smartphones are relatively affordable devices. With the increase in screen size and resolution, together with the improvements in performance of mobile CPUs and GPUs, more tasks have become possible. In this paper we explore the rendering of medium to large volumetric models on mobile and low performance devices in general. To do so, we present a progressive ray casting method that is able to obtain interactive frame rates and high quality results for models that not long ago were only supported by desktop computers.

show abstract

Adaptive transfer functions

Cited by 3 publications

References 25 publications

Real-time quality visualization of medical models on commodity and mobile devices

Real-time quality visualization of medical models on commodity and mobile devices

CGI 2016 Editorial (TVCJ)

Progressive ray casting for volumetric models on mobile devices

Contact Info

Product

Resources

About