Chapter title |
Predictive Modeling of Anatomy with Genetic and Clinical Data.
|
---|---|
Chapter number | 62 |
Book title |
Medical Image Computing and Computer-Assisted Intervention – MICCAI 2015
|
Published in |
Medical image computing and computer-assisted intervention : MICCAI ... International Conference on Medical Image Computing and Computer-Assisted Intervention, January 2015
|
DOI | 10.1007/978-3-319-24574-4_62 |
Pubmed ID | |
Book ISBNs |
978-3-31-924573-7, 978-3-31-924574-4
|
Authors |
Adrian V. Dalca, Ramesh Sridharan, Mert R. Sabuncu, Polina Golland |
Editors |
Nassir Navab, Joachim Hornegger, William M. Wells, Alejandro F. Frangi |
Abstract |
We present a semi-parametric generative model for predicting anatomy of a patient in subsequent scans following a single baseline image. Such predictive modeling promises to facilitate novel analyses in both voxel-level studies and longitudinal biomarker evaluation. We capture anatomical change through a combination of population-wide regression and a non-parametric model of the subject's health based on individual genetic and clinical indicators. In contrast to classical correlation and longitudinal analysis, we focus on predicting new observations from a single subject observation. We demonstrate prediction of follow-up anatomical scans in the ADNI cohort, and illustrate a novel analysis approach that compares a patient's scans to the predicted subject-specific healthy anatomical trajectory. |
Mendeley readers
Geographical breakdown
Country | Count | As % |
---|---|---|
United Kingdom | 1 | 5% |
United States | 1 | 5% |
Unknown | 17 | 89% |
Demographic breakdown
Readers by professional status | Count | As % |
---|---|---|
Student > Ph. D. Student | 6 | 32% |
Student > Master | 4 | 21% |
Researcher | 3 | 16% |
Professor | 2 | 11% |
Student > Bachelor | 1 | 5% |
Other | 0 | 0% |
Unknown | 3 | 16% |
Readers by discipline | Count | As % |
---|---|---|
Computer Science | 5 | 26% |
Engineering | 5 | 26% |
Medicine and Dentistry | 2 | 11% |
Agricultural and Biological Sciences | 1 | 5% |
Biochemistry, Genetics and Molecular Biology | 1 | 5% |
Other | 1 | 5% |
Unknown | 4 | 21% |