Research Interests
The focus of my research has been to develop new technologies that expand
the scope of medicine and increase the diagnostic capabilities of physicians
at the point of care.
Graduate Students
- Miguel Ossandon (2009, PhD Student) - Visual sensory substitution for
object avoidance.
- Xianshu Zhu (2009, MS Student) - Video summarization for laparoscopic
surgery.
- Ronil Mokashi (2009, 2010, MS Student) - Image classification with semantic
metadata in cell biology.
- Dashana Dalvi (2009, 2010, MS Student) - Image classification with semantic
metadata in cell biology.
- Justin Martineau (2010, PhD Student) - Image classification with semantic
metadata in cell biology.
- David Chapman (2010, PhD Student) - Image classification with semantic
metadata in cell biology.
Current Research Projects
-
Image Classification with Semantic Metadata in Cell Biology
Computational image classification is growing in importance in various
fields, including cell biology. We propose to develop a database that can
store images along with computer-extracted image features, and correlate these
features to metadata that captures biological or clinical characteristics. Our
initial focus is on the actin and myosin cytoskeleton. We are developing an
image classifier using a support vector machine to map image features to
biological characteristics. We are using the Oracle Relational Database
platform to leverage its ability to handle both multimedia and semantic data
efficiently. We are using a W3C semantic web approach to develop the ontology
for the biological characteristics.
-
Video Summarization for Laparoscopic Surgery
Laparoscopic surgery is a minimally
invasive technique that is the method of choice for a number of surgical
procedures. Patients who undergo laparoscopic surgery have smaller
scars, reduced pain, and a quicker recovery. The laparoscopic approach,
however, is more technical challenging and has more demanding training
requirements. Our overall goal is to develop a software tool to assist
with video-based assessment of surgical trainees. We are developing an
image classifier using machine learning approach to segment surgical
videos into their basic steps, perform time and motion
analysis, and provide a set of tools for review and
evaluation.
Wireless capsule endoscopy is used to directly visualize parts of the small
intestine previously unreachable by colonoscopy or upper endoscopy. As the
capsule travels through the digestive system, it collects in excess of 50,000
images, which must be reviewed by a gastroenterologist. We are developing machine learning
and image classification techniques to detect common lesions found in capsule
endoscopic studies.
-
Intelligent Software Agents for Disaster Management
An agent framework is being developed for the Department of Homeland Security to
support a peer-to-peer network of disaster responders using the
Unified Incident Command and Decision Support (UICDS) platform. This is a
middleware foundation that enables commercial and government incident management
technologies to share information and support decisions for the National
Response Framework and National Incident Management to prevent, protect,
respond, and recover from natural, technological, and terrorist events.
-
Virtual Reality Simulation for Medical Education
Virtual reality
environments such as Second Life are known to influence behavior. Learners
become immersed in their own education through three-dimensional realism,
role-play, and community interaction. We are using this approach to educate
people about specific medical issues and to virtually experience the benefits
and consequences of their behaviors. The educational areas we are working on
include diabetes and cancer prevention.
-
Personal Health Records
Personal Health Records (PHR) are health
records that are initiated and maintained by individuals. Examples of web-based
records include Google Health and Microsoft HealthVault. Issues related to PHRs
include trust, privacy, security, portability, mobility, medical identify theft,
fidelity and completeness of the medical record, and the ability to interface
with hospital-based and other clinical systems.
Past Research Projects
-
A Computerized Approach to Glycemic Control
Lessons learned from prior efforts were used to design an optimal approach
to computerize insulin protocols for critical care and general medicine
patients that better fits into the existing physician workflow.
-
Identification and Analysis of a TSH-Associated SNP
An analysis of a TSH-associated SNP was performed to help identify which
gene/variant was the most likely functional unit.
- Ventricular Assist Devices and Gastrointestinal Bleeding
A retrospective analysis of consecutive VAD recipients found that age was
the only independent predictor of gastrointestinal bleeding, and that
nonpulsatile VADs were not associated with an increase in gastrointestinal
bleeding versus there pulsatile counterparts.
-
Efforts to Minimize Adverse Events by Cross-Covering Physicians
An analysis of process improvement efforts regarding on the transfer or
care was performed, and a software framework was developed to increase the
accuracy and safety of this process.
-
Medical Response to Terrorist Attacks and Other Disasters
A redundant communication framework was developed to mobilize medical
personnel and transfer information during a medical disaster.
- Clinical Trials Data Collection Using Palm Computers
A handheld data collection system was developed to update and validate
clinical information obtained at the bedside or in the field.
- Voice-Driven Pathology Data Management System
A voice-driven system was developed to collect clinical data in hands-busy
and eyes-busy environments.
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