Medical Image and Computational Analysis Lab


Walter O'Dell, PhD; Faculty Member

Under the direction of Dr Walter O’Dell, Assistant Professor, the Medical Image and Computational Analysis Lab (MiaCaLab) in the Department of Radiation Oncology is interested in discovering and applying novel image analysis and image-based computational techniques for improved detection, follow-up, and treatment of cancer.

Much of the work is highly translational, with direct application to the treatment of patients within the Department of Radiation Oncology.


Projects

Vascular Tree Structure/Function – Segmenting and Characterizing Pulmonary Vasculature Tree Structure

Involves analysis of pulmonary vascular development in human neonate with extreme pre-term gestation. Applying non-invasive assessment of pulmonary vascular structure to quantify (1) the response of the lung to radiation exposure in breast cancer patients (funded through a grant from the Florida Department of Health); (2) the development of lung vasculature in children born extremely prematurely; and (3) changes in vascular anatomy adults and in rat lungs with various vascular diseases.

Small Tumor Detection with 3D Template Matching – Imaging for Metastatic Breast Cancer Early Detection

Two surveillance imaging studies for high-risk breast cancer survivors. The first study is funded by the Ocala Royal Dames for Cancer Research. The second study is funded through the Florida Academic Cancer Center Alliance.

MR Cardiac Tagging – MR Cardiac Tagging for Quantitative Assessment of Heart Function

Using software for computer-assisted contouring of the heard, 3D heart surface modeling, and a new approach for tag-based motion reconstruction using a deformable image registration approach and virtual tagged images to quantify acute and chronic changes in myocardial function in breast cancer patients who receive RT to the chest wall.

Lung Radiation Dose Response

Applying quantitative analysis of follow-up CT chest scans of patients after targeted radiation treatment to correlate directly the progression of fibrosis with the amount of radiation dose delivered during treatment in an effort to validate and compare the effectiveness of agents used to protect normal tissues (and accelerate recovery) both in animal models and in human subjects.