Current Research Project Listings:
The following abstracts detail the current research projects in this
group. All projects are under the supervision of A.P. Reeves:
Computer Vision and Medical Image Analysis
Early Lung Cancer Detection from Pulmonary CT Scans
GGO Characterization
Lung Analysis from CT Screening Studies
Dysplastic Hips in Post-Natal Femur
Emphysema Quantification and Analysis of Progression
Vessel Width Tracking
VIA Research Summaries:
Early Lung Cancer Detection from Pulmonary CT Scans
Automated pulmonary nodule detection involves
identifying the location of pulmonary nodules in whole lung CT scans
using computer methods without any intervention of a radiologist or
other personnel.
(Full Abstract)
Principal Research Student: Sergei Fotin
GGO Characterization
Improvements in CT technology and increasing number of accumulated cases have allowed radiologists to find a new type of
abnormality, referred to in the literature as GGO or subsolid nodule.
These abnormalities have radiological appearances and malignancy rates that
are different from those of solid nodules. Characterization of the
subsolid nodules could lead to better knowledge about their evolution
and better screening protocols.
(Full Abstract)
Principal Research Student: Andrew Browder
Lung Analysis from CT Screening Studies
The goal of this reseach is to
develop computer algorithms to analyze whole lung CT scans from lung
cancer screening studies. Lung cancer screening is poised to become a
major practice in the near future. As long as patients are undergoing
radiation for early lung cancer detection, it is only logical to analyze
the same images to diagnose other diseases. Currently, computer algorithms have been developed to perform lung
segmentation, lung volume measurements, and the detection and visualization of
emphysema. These algorithms are automated, requiring no
human interaction or assistance.
(Full Abstract)
Principal Researcher: Artit Jirapatnakul
Dysplastic Hips in Post-Natal Femur
Osteoarthritis is the leading cause of adult disability in the
United States. Approximately 40% of idiopathic osteoarthritis (OA)
cases can be attributed to developmental dysplasia of the hip
(DDH). While the endstage OA has been the subject of much
research, little is known, about the early postnatal development
of the dysplastic hip. The objective of this research is to
quantitatively describe the temporal development of normal and
dysplastic hips.
(Full Abstract)
Principal Research Student: Wendy Vandenberg-Foels
Emphysema Quantification and Analysis of Progression
Emphysema is clinically defined as abnormal enlargement of the air spaces in the lung. Standard automated emphysema quantification from Computed Tomography images involves thresholding at a certain H.U. density level, and taking the percentage of lung parenchyma below that density. This defines the Emphysema/Pixel Index which is the most common measure of emphysema in patients from CT images. The Emphysema Index, however, has several disadvantages in practice. This research is directed at developing an improved method of quantification, using to minimize these disadvanteges.
(Full Abstract)
Principal Research Student: Brad Keller
Vessel Width Tracking
Measuring the vessel diameters over time is a crucial step
in studying the effect of various stimuli on the
width of blood vessel nearby. However, it is a
time-consuming task because the measurement is done for
hundreds of image frames.
The goal of this research is to relieve this burden
by automating the blood vessel measurements throughout the sequence
of image frames.
(Full Abstract)
Principal Research Student: Jaesung Lee