Institute for
Biomedical Informatics

Dr. Jin Chen receives two-year funds from NCI to standardize and normalize CT images for lung cancer patients. Computed tomography (CT) is one of the most popular diagnostic image modalities routinely used for assessing anatomical tissue characteristics for disease management. However, CT images are often acquired using scanners from different vendors with different imaging standards, posing a fundamental challenge to radiomic studies across sites. The goal of the Standardization and Normalization of CT images for lung cancer patients (STAN-CT) project is to develop a deep learning software package that can automatically standardize and normalize a large volume of chest CT images to facilitate cross-site large-scale image feature extraction for lung cancer characterization and stratification.

A new journal article, Identifying emerging phenomenon in long temporal phenotyping experiments, from Dr. Chen's group describes an algorithm to identify emerging phenomemna, i.e., a group of genotypes who exhibit a coherent phenotype pattern during a relatively short time period, from from large-scale temporal plant phenotyping experiments.  The paper was published in Bioinformatics, a leading journal in the field.

Work by Melissa Clarkson and Steve Roggenkamp presented at the 10th International Conference on Biomedical Ontology.

Two papers from the BMI Associate Professor Qiang Cheng's group have been accepted by IEEE CVPR2019, June 16th - 20th 2019, the premier annual computer vision conference.

Rama Kavuluru, PhD, has joined the editorial board of the Journal of Biomedical Informatics, a journal devoted to publishing new biomedical informatics methodologies.

The AMIA 2018 Annual Symposium will be held in San Francisco, November 3–7. Accepted work from IBI members will be presented as oral presentations, system demonstrations, posters, and in pre-symposium working groups.