Mehul Sampat, Ph.D. 2006

Mehul Sampat1

Why This is an Exciting Time for Medical Imaging: 5 Questions Senior Software Engineer Mehul Sampat

Mehul Sampat, a senior software engineer at BioClinica in the San Francisco Bay Area, received his Ph. D. from UT Austin in 2006 and chose industry over academics. He grew up in Mumbai, India where he got his undergraduate degree in one of the first programs to offer biomedical engineering.

What do you do at BioClinica?

BioClinica provides centralized imaging services for neurology, musculoskeletal and oncology clinical trials. We help pharmaceutical companies conduct clinical trials by collecting images and making measurements on those images. These imaging-based measurements are vital for the approval of new drug. For example, in an Alzheimer’s trial, we analyze scanned images of the brain to measure the change in brain volume over time. These quantitative measurements provide evidence for the effectiveness of the medication. Bioclinica is a key contributor in the drug development process. I work in the research and development team, which implements and integrates quantitative methods into a production system in which millions of medical images have been collected and analyzed over the last 20 years.

What prompted to you to choose industry over academia?

I had originally started in academia by working in the neurology department at University of California San Francisco. Over time, I was curious to learn how the great work done in academia is applied in real world industry scenarios. I started looking into engineering positions, specifically in medical imaging focusing on magnetic resonance imaging, (MRI), computed tomography (CT) and ultrasound. The opportunity at BioClinica was a perfect fit for me.

What excites you about the future of the industry you’re in?

Ever since I was an undergrad, I’ve found medical imaging and quantitative data analysis fascinating. This is one of the most exciting times to be working in the field of medical image analysis. In particular, various advancements have been made in a specific area of machine learning, called Deep Learning. Deep learning-based techniques have essentially revolutionized the field of medical image analysis. Using deep learning-based segmentation techniques, we can now make more accurate measurements of various organs in the body such as the liver and spleen. In addition, deep learning-based techniques can also help classify images as malignant or benign an make a recommendation to an expert physician.

These advancements will eventually help bring higher quality of medical care to the general population. In addition, in countries with a shortage of radiologists and other expert physicians, these methods can be used to screen a large number of patients and detect early signs of disease.

What were some of your most memorable experiences at UT Austin?

I met my wife at UT Austin. She and I are from the same city back in India but we met here in Austin, back when electrical engineering and biomedical engineering were in the same building.

I went to UT Austin at the same time we won the national football championship in 2005, and it was an unbelievable experience. People were dancing in the streets.

How did your time at UT prepare you for industry work?

I was interested in medical imaging and started working with Dr. Alan Bovik for my master’s degree and then my Ph.D. work was co-supervised by Dr. Mia Markey and Dr. Alan Bovik. During my Ph.D, I worked on developing an algorithm for the computer-aided detection of breast cancer from x-ray images. Dr. Markey was an ideal mentor for me as she is an expert in the areas of computer aided detection and medical imaging. In addition, Dr Bovik, is an expert in image analysis, and I was extremely fortunate to have this perfect combination of mentors!

UT Austin offers students the flexibility to explore classes in other departments and then apply that knowledge to their specific tasks in biomedical engineering. For example, both the Digital Imaging Processing and Pattern Recognition courses were invaluable during my graduate work, and they have helped prepare me for my position in industry.

Another course I highly recommend for all students is the Bio-statistics course that was created by Dr. Markey. It teaches the fundamentals of statistics that are invaluable in all domains.