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My interest in medical imaging research came as a surprise to me as it was not a path
that I have envisioned at the beginning of my undergraduate career. In retrospect, I see
how my undergraduate and graduate studies have led me into this area of research and
how it suits me perfectly.
Inspired by my mother’s career as a chief physician at a hospital, I enrolled in the
undergraduate biomedical engineering program at Xi’an Jiaotong University, an
excellent institution in this field, with a keen interest in applied physics and math. I was
thrilled to apply the knowledge I learned in class to design creative devices such as
MCU-based heart rate monitor as well as an EEG-controlled music player for people
with Alzheimer’s disease. Research is about more than just carrying out experiments
and designs; it is a complicated process of intellectual questioning and discovery.
Keeping this lesson in mind, I found that the user’s attention has a large impact on the
functioning of my player design and was inspired to investigate the impact of
attentiveness based on corticomuscular coherence. As the team leader of these projects,
I not only laid out the overall research design, but also took charge of organizing group
work and managing our budget. I gradually honed my innovative thinking and
leadership skills. I truly enjoyed the accomplishment of query, discovery, and
converting technology into the field of healthcare.
Luckily, I was chosen for a summer internship at Philips Healthcare in my junior year,
where I received training on MRI principles and pulse sequence design. I was
mesmerized by the perfect physical laws and elegant math hidden in the hollow cylinder.
Following this long last interest, I joined Professor Bai Lijun’s Lab in functional MRI
analysis for my thesis. Reading a variety of papers taught me that aging is a heated topic
in neural imaging research, so I conducted an independent project to investigate the
intervention mechanism of mild cognitive impairment (MCI). I proposed combing the
structural analysis of DTI with the functional analysis of fMRI-BOLD to reveal the
functionality and connectivity transformation of the brain. To modify my method, I
analyzed previous studies and taught myself various image processing and analysis
techniques such as tract-based spatial statistics (TBSS) and Small-World Networks.
This experience allowed me to become an independent researcher. Meanwhile, I was
intrigued by the beauty of MRI and its essential role in diagnosis and treatment, and it’s
more appealing for me to see how MRI is applied in clinic since it makes research come
true. Driven by this curiosity, I completed an internship in the Department of Radiology
and Radiation Oncology at the First Affiliated Hospital of Xi’an Jiaotong University.
Shadowing with the medical physicists, I found that the image-guided radiation therapy
(IGRT) technology is a perfect fusion of MRI with clinical use, and this is what I want
to pursue.
With a strong interest in MRI, I entered Duke University’s Medical Physics Graduate
Program. I am excited about MRI applications, especially in radiation therapy, because
of its superior soft-tissue contrast for tumor imaging and its strong potential for daily
imaging without radiation dose, which could bring evolution to the clinic. In this
topnotch program, I took advanced courses to gain expertise with difference MRI
applications and radiation therapy concepts. The practicum courses gave me clinical
experience with a variety of both radiation therapy procedures and imaging techniques
such as MR, CBCT, and PET, which have enriched my comprehension of MRI and
IGRT. For example, to obtain a better understanding of IGRT key concepts, I took over a project to achieve a Digitally Reconstructed Radiography (DRR) generation
algorithm from planning images, and designed rigid image registration program
between DRR and on-board images to acquire coordinate shift information. It was
challenging but thrilling to transform this theoretical concept, which was a ‘black box’
that I only used in commercial software, into an actual practice. Although this
implementation was only practiced on a simple pelvis phantom, the work enriched my
comprehension of the translation of image techniques.
My interest in MRI translation and IGRT led me to join the research group of my
advisors Dr. Jing Cai and Dr. Lei Ren. The work for my thesis research involves
developing a retrospective sorting method of 4D-MRI with diaphragm profile-based
respiratory surrogate to improve respiratory motion management in radiation therapy.
My work aims to reduce stitching artifacts, which is inherent in 4D images based on
classic sorting methods. The first challenge that I encountered was extracting the
anatomic information of the diaphragm from orthogonal MRI images. After reviewing
papers on existing methods, I designed a region growing auto-segmentation method.
However, in a practical situation, the actual patient data would have greater complexity
than a digital phantom, which would influence the accuracy of the landmark
information. Through detailed analysis, I found that cross correlation, a commonly used
metric for image registration, would be an excellent method for reducing the
uncertainties in implementing landmark matching in order to reconstruct 4D images.
Currently, I am testing the robustness of this method with irregular breathing signals
and trying to optimize it further. Research involves solving a series complicated
problems and this project further strengthened my skills at doing so. My fascination
with the translation of MRI into clinical applications also grew further and it is my
motivation for pursuing a PhD in medical imaging.
From all of these experiences, I have developed a strong interest in research and a
passion for becoming a research scientist in translational imaging research in clinic.
The systematic research training I will receive as a PhD student will enable me to pursue
this goal. With a clear objective, I am eager to continue my PhD research at Yale
University, which offers diverse imaging research which are closely related to clinical
practice, such as Dr. Todd Constable’s and Michelle Hampson’s research on functional
neuroimaging, Dr. Dana C Peters’s research interest in cardiovascular MRI
development, Dr. Lawrence H. Staib’s project about image analysis, and Dr. Chi Liu’s
group in PET/CT and SPECT/CT technology development. However, I would also be
interested in joining another imaging related group. My training and background in
medical physics and biomedical engineering have prepared me well for the
requirements of a PhD student majoring in biomedical engineering. The PhD program
at Yale University will allow me to apply my talent and skill to become a leader in the
field of medical imaging.

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