Faculty Profile - University of Houston
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Faculty Profile

Mini DasMini Das

Associate Professor
Department of Physics
Department of Biomedical Engineering

Office: Science & Research 1, 419B
Contact: mdas@uh.edu - 713-743-3539

Education: Ph.D., Indian Institute of Technology, Delhi

Group Website
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I am an Applied Physicist and an Engineer who works at the interface of multiple disciplines to solve outstanding challenges in medical and biological imaging. We combine tools and techniques from optical physics, applied mathematics, cutting edge instrumentation, analytical methods and extensive computational platforms. The broader impact and applications of my group’s work are in multiple areas besides biological and medical imaging, such as in defense/security, materials imaging, quantitation and characterization in chemical, materials and geophysical imaging problems. We are also very motivated to explore fundamental aspects related to light-matter interactions via quantum detection and other cutting edge tools being developed in my lab. Some of my key interests are : Experimental/Optical design and computational imaging for advanced and innovative imaging methods, computational simulation platforms for “virtual clinical trials”, psychophysics/image science aspects, vision science as well as global health/cancer screening to help bring cancer screening and imaging to underserved population and third world countries. These are detailed below.

  1. Design and development of advanced imaging techniques – involves optical/benchtop x-ray experiments and computational imaging. Optical physics concepts are effectively combined with advanced algorithms and technological advances such as spectral and quantum detection via single photon counting detectors to extract hidden contrast and to quantitate maps of materials/contrast agents/tissue types. We closely collaborate with scientists and engineers at CERN (Geneva) to optimize and develop the next generation quantum detectors. Modalities of interest: X-ray, optical, ultrasound and thermal imaging. Fully and partially tomographic imaging for breast cancer detection is tested in collaboration with clinical and industrial partners.
  2. Extensive computational simulation platforms are being developed for several emerging and recently approved medical imaging systems. This involves forward modeling using rigorous physics of light matter interaction as well as analytical or Monte Carlo methods. These developments can be categorized under Virtual Clinical Trial which is encouraged by the regulatory agencies such as the Food and Drugs administration (FDA). The key goal is to test new imaging system and algorithm designs (also can include image processing tools) using task based assessment methods using realistic computational platforms and 3D digitized virtual patients (or organs). Other requirements include accurate modeling of signal gain, distortions and noise properties in semiconductor area detectors used. Developed platforms are validated with experiments. Using an ensemble of patient models, one can now realize an array of images generated by varying multiple parameters without the time and effort (or subjecting to additional radiation dose) of imaging a large population. A critical part of this work is developing image reconstruction methods and processing algorithms that are dose efficient and enables better signal detection performance.
  3. Psychophysics and Image Science: Psychophysical experiments and understanding image features that drive human observer’s perception is critical in developing novel systems. Examples of such decision making stages include perception of a radiologist who is assessing medical images or a human observer assessing x-ray images in transportation security. The process of making decisions regarding location and detection of signal or targets like cancers in a complex, heterogeneous and turbid medium is yet to be completely understood. We employ studies where image and noise features are evaluated via quantitative metrics. These include second order statistical texture features and noise power spectral parameters. We experiment with observer performance experiments in our laboratory with eye tracking systems to advance knowledge and build models for these problems. We also collaborate on the development of computational models that would match human observer performance.
  4. As a combination of the above avenues, we are exploring the feedback mechanism from vision science and psychophysics to develop more efficient optical and imaging systems, detectors and cameras. These would fall broadly under bio-inspired optical and imaging system designs.
  5. We are seeking collaborations with other scientists, engineers and clinicians to compliment our expertise and together tackle some unmet needs in cancer and biological imaging. One of our key goals is also to facilitate emerging imaging technologies to reach underserved populations in the nation and across the world at a faster pace than it normally happens. To this end we are working with non profit organizations and aim to educate and bring cancer screening to underserved populations both locally and internationally.

Awards & Honors

NSF Advance leadership Fellow at the University of Houston (2019)

Award for excellence in Research and Scholarship (University of Houston) (2018)

National Science Foundation CAREER Award (2017)

Department of Defense Breakthrough Award (Congressionally directed Medical Research Program (CDMRP) (2016)

Career Development Award (K25) (2009) National Cancer Institute (NCI) division of the National Institutes of Health (NIH)

Organizations, Outreach, Boards, Memberships

Memberships

American Physical Society (APS)
Institute of Electrical and Electronics Engineers (IEEE)
Society of Optics and Photonics (SPIE)
Optical Society of America (OSA)
Biomedical Engineering Society (BMES)

Outreach

Ace Cancer Care (Non-profit organization for free cancer screening, awareness and education)
Research Experience for undergraduate and high school students

Boards

Associate Editor for Medical Physics
Associate Editor for IEEE Transactions on Medical Imaging