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I am interested in pursuing a PhD program in biomedical engineering with a
specialization on biomedical imaging. In particular, I would like to work on developing new
non-invasive imaging and computational analysis techniques in order to study and diagnose
diseases. For me, it is a fascinating area as it combines mathematical modelling, physics,
signal and image processing, and medicine. A PhD program in this area is a cornerstone in
my long-term goal of becoming a faculty member in the area and improving health care.
From the early days of my studies, I have been excited by the idea of an academic career.
During my junior year in my electronic engineering undergraduate studies, I had the
opportunity to participate in several projects on digital signal and image processing that
competed in several national project contests. On my sophomore year, I attended a
conference where I was impressed with the wide range of applications that electrical
engineering and signal processing could have on medical practice. It was then when I
decided that I wanted to specialize on biomedical engineering. For my undergraduate thesis,
I developed a recognition system of laryngeal electromyography signals for control. This
work was later published in IEEE Latin American Transactions.
Wanting to specialize in biomedical engineering, I applied and was accepted into a fully
funded PhD program in the USA. Unfortunately, due to a personal loss, I had to reject the
offer and stay in Peru to support my family. This did not keep me from pursuing my career
goals, even though I stayed in Peru, I continued my education in biomedical signals at PUCP,
where I entered a Masters program and was given the opportunity to work as a research
assistant in the Medical Imaging Laboratory under the supervision of Professor Roberto
Lavarello. Here, I diversified my background and gained experience in linear systems,
biomedical imaging, signal processing, machine learning, inverse problems and
optimization. More importantly, I was able to grasp the importance of developing novel
imaging modalities as means to improve diagnoses and to gain a deeper understanding of
diseases: for instance, by improving the resolution and contrast of ultrasound images we
could see pathological hypoechoic structures or small reflectors that would otherwise be
overlooked.
This year, I successfully defended my master’s thesis on the development of new
adaptive beamforming technique for medical ultrasound images. This technique integrates
phase aberration correction (a way to correct ultrasound wave distortion) into an adaptive
beamformer (a method for improving resolution and contrast). The developed technique
improves performance over the state-of-the-art and might be useful, for example, in
microcalcification detection in breast screening. I have presented this research at two
conferences: the 2016 IEEE Engineering in Medicine and Biology Society Conference and the
2016 International Ultrasonic Symposium. Additionally, I have first-authored one journal
article published this year in Ultrasonic Imaging and I am preparing the resubmission of a
second journal article to the IEEE Transactions on Ultrasonics, Ferroelectrics, and
Frequency Control.
Additionally, as this thesis project was a joint effort between PUCP and Stanford
University (co-supervised by Professor Jeremy Dahl), I have had the opportunity to spend
three months as a visiting research student in the Department of Radiology at Stanford.
Aside from working on the experimental part of my thesis, I also participated in another
project with Dr. Dahl’s Stanford team on the estimation of speed of sound maps in tissue with pulse-echo ultrasound.This was an interdisciplinary endeavor that involves experts in
ultrasound, in x-ray and CT, and pediatric clinicians. The application is to noninvasively
assess Nonalcoholic fatty liver disease (NAFLD) and nonalcoholic steatohepatitis (NASH),
two diseases difficult to identify even with biopsy. This was an interdisciplinary endeavor
that involved engineering experts in ultrasound, x-ray, and CT, as well as pediatric clinicians,
and was presented at the 2016 Ultrasonic Imaging and Tissue Characterization Symposium.
In addition, I have also worked on the automatic detection of B-lines (artifacts normally
related to pneumonia) using AM-FM features and machine learning algorithms. This project
is aimed at providing more automated procedures for pneumonia diagnosis in pediatric
populations for rural zones of Peru.
After finishing my master’s, I continued working on the digital signal processing
laboratory at PUCP, where I increased my experience on image processing, inverse problems
and optimization techniques. I have presented a novel fully incremental robust
background/foreground separation algorithm at the International Conference on Computer
Vision and I have also developed new faster algorithms for mixed norm regularization
problems. I have also worked on my own on neural signal processing. This year, I have
presented an abstract at the annual meeting of the Society for Neuroscience (SfN) detailing a
cross-patient seizure detection system in EEG recordings using deep learning. I won a
Trainee Professional Development Award from the SfN that allowed me to attend and
present my work.
Looking forward, I want to continue my research career on medical imaging and image
processing, by developing new imaging and analysis techniques, and I am convinced that
Yale University is the optimal place to follow my goals. In particular, I am interested in the
research being conducted by professor professor James Duncan on image analysis for
cardiovascular and brain structure applications, in the work of professor Todd Constable on
novel fMRI and quantitative analysis techniques to study brain function, in the research of
the research of professor Fahmeed Hyder on translational fMRI to study metabolism and
brain disorders, and also in the research of professor Hemant Tagare on heart motion
analysis.
In summary, I believe that with my background in signal processing and medical
imaging, I would thrive in your program. I am convinced that Yale is an optimal place to
continue my studies as it combines the strengths of one of the best medical schools in the
world with state-of-the-art engineering research, and this unique mixture would allow me
not only to develop new imaging technologies but also to be able to translate them into
clinical practice and make a real impact in the quality of healthcare.

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Hi!
I'm Katherine!

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