PubMed Health⌕ Search
Home/Archive/PubMed

PubMed · 8177164

Computerized three-dimensional segmented human anatomy.

I G Zubal·C R Harrell·E O Smith·Z Rattner·G Gindi·P B Hoffer
View original source ↗Export metadata ↓

Abstract

Manual segmentation of 129 x-ray CT transverse slices of a living male human has been done and a computerized 3-dimensional volume array modeling all major internal structures of the body has been created. Each voxel of the volume contains a index number designating it as belonging to a given organ or internal structure. The original x-ray CT images were reconstructed in a 512 x 512 matrix with a resolution of 1 mm in the x,y plane. The z-axis resolution is 1 cm from neck to midthigh and 0.5 cm from neck to crown of the head. This volume array represents a high resolution model of the human anatomy and can serve as a voxel-based anthropomorphic phantom suitable for many computer-based modeling and simulation calculations.

Explore related subjects

Computer SimulationHumansMaleModels, AnatomicModels, StructuralJournal ArticleResearch Support, U.S. Gov't, Non-P.H.S.

Keep this discovery

Explore connections, maps & timelines

BibTeXRIS

I G Zubal, C R Harrell, E O Smith, Z Rattner, G Gindi, P B Hoffer. 1994. Computerized three-dimensional segmented human anatomy.. https://doi.org/10.1118/1.597290

Cite the original work for its findings. Save a collection to share your selection of sources.

KEEP EXPLORING

Related citations

PubMed2025

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation↗
PubMed2017

Addressing current challenges in cancer immunotherapy with mathematical and computational modelling.

The goal of cancer immunotherapy is to boost a patient's immune response to a tumour. Yet, the design of an effective immunotherapy is complicated by various factors, including a potentially immunosuppressive tumour microenvironment, immune-modulating effects of conventional treatments and therapy-related toxicities. These complexities can be incorporated into mathematical and computational models of cancer immunotherapy that can then be used to aid in rational therapy design. In this review, we survey modelling approaches under the umbrella of the major challenges facing immunotherapy development, which encompass tumour classification, optimal treatment scheduling and combination therapy design. Although overlapping, each challenge has presented unique opportunities for modellers to make contributions using analytical and numerical analysis of model outcomes, as well as optimization algorithms. We discuss several examples of models that have grown in complexity as more biological information has become available, showcasing how model development is a dynamic process interlinked with the rapid advances in tumour-immune biology. We conclude the review with recommendations for modellers both with respect to methodology and biological direction that might help keep modellers at the forefront of cancer immunotherapy development.

Computer Simulation↗
PubMed1996

Eradication of poliomyelitis: when can one be sure that polio virus transmission has been terminated?

Most polio virus infections are silent. Vaccination reduces the incidence of infection, and the period between clinical cases of poliomyelitis becomes longer. As the point of eradication is approached, it becomes increasingly difficult to use the case-free period to determine whether silent infections have ceased. In this paper, the authors use stochastic computer simulations to relate case-free periods to the presence or absence of silent infections. After 2 years without paralytic cases in a population of 200,000 inhabitants, the probability for the presence of silent infections can still be as high as 38%. The case-free period must exceed 3 years before one can be 95% certain that there has been local extinction of the wild polio virus infection. Even after 5 years without cases, the probability of silent polio virus transmission can still be in the range of 0.1-1.0%.

Computer Simulation↗