My name is Yiyun Gu and I am a fourth-year student studying mathematics and statistics at University of Toronto. After taking some statistical courses and machine learning courses, I was quite interested in applying machine learning methods and statistical methods to practice. Medical imaging is a popular field where machine learning methods have great impacts. Therefore, I contacted Dr. Pascal Tyrrell and he would like to supervise me.

Last September, my initial research direction was Bayesian optimization on hyperparameters of Convolutional Neural Networks based on the previous model information and the distributions. Besides Dr. Pascal Tyrrell’s instruction, he introduced his graduate student who was also interested in this field. We had weekly meetings to discuss how to make the idea implementable. I read many papers and learned relevant knowledge of Gaussian process, acquisition functions and surrogate functions. However, there was a huge challenge on how to update the hyperparameters of the prior distribution based on the information from the CNNs model. I was anxious about the progress. Dr. Pascal Tyrrell encouraged me to shift the direction a little bit because he cared about what a student learned and felt about the project.

Since November, out of interest in Bayesian concepts, I have been working on a project about comparing frequentist CNNs and Bayesian CNNs for the projects with sample size restrictions. Because there might not be sufficient data in medical imaging, I would like to determine whether Bayesian CNNs would benefit from prior information for small datasets and outperform frequentist CNNs. Bayesian CNNs update the distributions of weights and bias while frequentist CNNs use point estimates. The resources of the codes of Bayesian CNNs were limited. I tried to make full use of and modify the codes so that I could run the experiments from training sample size equal to 500 to training sample size equal to 50000. I applied customized architectures and AlexNet to MNIST and CIFAR-10 datasets. I found out that Bayesian CNNs didn’t perform well as I expected. Frequentist CNNs achieved higher accuracy and took less time compared to Bayesian CNNs. However, there is an interesting feature of Bayesian CNNs. Bayesian CNNs incorporate uncertainty measure. Since Bayesian CNNs have the distributions of weights, the models can also output the distributions of outputs. Therefore, Bayesian CNNs could tell how confident the decision is made.

I hope to apply more architectures of Bayesian CNNs to more datasets in medical imaging projects because architectures and datasets have great influences on the performance. Also, I would like to try more prior distributions and learn how to determine which distributions are more appropriate.

I had great research experience in this project with Dr. Pascal Tyrrell’s guidance and other graduate students’ help. It was my first time to write scientific report. Dr. Pascal Tyrrell kept instructing me how to write the report and offered great advice. I really appreciated the guidance and enjoyed the unique research experience in the end year of my undergraduate life. I look forward to contributing to medical imaging research and more opportunities to apply machine learning methods!

Yiyun Gu

Amar Dholakia: Some Thoughts as I Wrap Up My STA498Y Project (and Undergrad!)

Hi everyone! I’m Amar Dholakia and I’m a fourth-year/recent graduate having majored in Neuroscience and Statistics, and am starting a Masters’ in Biostatistics at UofT in the fall of 2020. I’ve had the pleasure of being a part of Dr. Tyrrell’s lab for almost two years now and would like to take the opportunity to reflect on my time here.

I started in Fall 2018 as a work-study student, tasked with managing the Department of Medical Imaging’s database. A highlight was discussing and learning about my peers’ work, which sparked my initial interest in the field of artificial intelligence and data science.

The following fall, I began a fourth-year project in statistics, STA498Y under the supervision of Dr. Tyrrell. My project investigated the viability of clustering of image features to assess dataset heterogeneity on deep convolutional network accuracy. Specifically, I compared the behaviour of six clustering algorithms to see if the choice of algorithm affected the ability to capture heterogeneity.

My project started out with reaching out to my labmate and good friend Mauro Mendez, who had recently undertaken a project very similar to mine. He sent me his paper, which I read, and re-read, and re-re-read… It took me about four months to only begin to grasp what Mauro had explored, and how I could use what he had learned to develop my project. But months of struggle was definitely worth the “a-ha!” moment.

First I started by replicating Mauro’s results using Fuzzy K as a clustering to make sure I was on the right track. Reading, coding, and testing the very first time was a nightmare – I had some Python experience but had never applied it before. It took a lot of back and forth with Mauro and Dr. Tyrrell , a lot of learning, understanding, and re-learning what I THOUGHT I understood to get me on the right track. By the start of the Winter term, I had finally conjured preliminary results – banging my head on the wall was slowly becoming worth it.

Once I had the code basics down, getting the rest of the results was relatively smooth sailing. I computed and plotted changes in model accuracy with sample size, and heterogeneity in model accuracy with sample size, as captured by different clustering methods. My results for one model were great from the get go – I was set! I thought to challenge myself by generalizing to a second model – and that was far from easy. But by taking that extra challenge, I felt I learned more about my project, and importantly, how to scientifically justify my results. The results didn’t match up, and I had to support my rationale with evidence (from the literature). If I couldn’t find an explanation, I may have done something incorrectly. And lo and behold, my ‘inexplicable’ results were in fact due to human error – something I very painstakingly troubleshooted, but now I understand much more and justify.

Ultimately, we showed that regardless of clustering technique, or CNN model, clustering could effectively detect how heterogeneity affected CNN accuracy. To me, this was an interesting result as I expected vastly different behaviour between partition-based and density-based

clustering. Nonetheless, it was welcome, as it suggested that any clustering method could be used to assess CNN.

I struggled most with truly appreciating what my research aimed to solve. I attribute this partially to not being as proactive with my readings and questions to Dr. Tyrrell to really verify my understanding. And to be honest, exploring this project is still a work-in-progress – something I will continue learning about this summer!

My advice to any future students – read, read, read! Diving into a specific academic niche is truly a wonderful experience. The learning curve was steep and initially involved a lot of trying, failing, fixing, and then trying again. But this experience only reinforced my notions of “success through failure” and “growth through struggle”. It may be challenging at first, but with some perseverance and support from a wonderful PI – like Dr. Tyrrell – you’ll be able to accomplish so much more than you originally imagined.

Sharing Medical Images for Research: Patients’ Perspectives

Michelle was our second YSP student this summer and did a great job at particpating in one of our studies in looking at patients’ willingness to share their medical images for research. This study is also part of the MiNE project.

Here is what Michelle had to say:

“My name is Michelle Cheung and I am a rising senior at Henry M. Gunn High School in Palo Alto, California. In my free time, I love to bake, read, travel with family, and take Barre classes. I also enjoy volunteering with friends at local charitable events and the Key Club at school. I am very interested in human biology and hope to study genetics and biotechnology next fall.

I really enjoyed the three weeks with the YSP Research Program. I learned so much about medical imaging modalities and had the amazing opportunity of helping research assistants survey patients at the Sunnybrook Hospital for the MiNE project. At first, it was a little daunting, but over time, I became more confident and comfortable interacting with patients, and grew to love surveying. The continuous surveying each day highlights the aspect and importance of repetition in conducting scientific research. Above all, it was an absolute pleasure getting to know the MiDATA and VBIRG lab. I’m grateful to my mentors and the lab members for exposing me to a whole new lab world I never thought existed beyond the traditional wet labs.”

Great job Michelle!

Have a peek at Michelle’s award winning poster and…

… I’ll see you in the blogosphere.

Pascal Tyrrell

Wow! What a Busy Summer….

Over 20 students in the lab this summer beavering away at some great projects. Last week my two Youth Summer Program (University of Toronto) students finished their three week stay with us. 

Jenny and Michelle both did fantastic work.

Today Jenny will show you her poster entitled:“Comparing Healthy and Unhealthy Carotid Arteries”

Jenny Joo is from Richmond Hill, Ontario, entering her senior year of high school. She plans on studying life science at the University of Toronto in the future. She spent the last 3 weeks in U of T’s YSP Medical Research program, where she was placed in two different medical imaging labs: The MiDATA lab of U of T and the Vascular Biology Imaging Research lab at Sunnybrook Hospital. 
Jenny chose to do research on the MRI scans of the carotid artery because it focused on both research and clinical aspects and had this to say about her experience with us: “It has been an enriching 3 weeks working with my PI, Pascal Tyrrell, my mentors, John Harvey and Moran Foster, and the rest of the research group.” 

Great work Jenny Joo!

Have a peek at her poster and…
… I’ll see you in the blogosphere.

Pascal Tyrrell

Engaging Primary Care in Research: Not Always an Easy Task

I am Stella Bing Xin Song, currently a second year student studying pharmacology and psychology at University of Toronto. I was fortunate to be a part of the 2016 Research Opportunity Program (ROP) supervised by Dr. Pascal Tyrrell in the Department of Medical Imaging at University of Toronto. 
My ROP project focused on evaluating the feasibility of using MRI as the primary imaging modality for carotid artery stenosis diagnosis and assessment (not sure what we are talking about? See previous posts here and here). Along with Ginni Ting, a student volunteer in Dr. Tyrrell’s lab, we surveyed physicians in the Niagara region of Ontario to learn about their perspectives on this proposal. Our community partner in this research was Heart Niagara – a fantastic local organization that has been guiding advances in cardiac health education and services since 1977.
Most of the responding physicians saw approximately 2000 or more patients per year. Physicians expressed a variety of care-related decisions for carotid artery stenosis patients, especially for those where diagnosis was less obvious with less than 70% stenosis. Most responding physicians would consider MRI over Ultrasound as the first-line diagnostic imaging modality, because of its ability to detect IPH yielding more pertinent information. IPH is bleeding within the plaques, which causes them to become more vulnerable (see vulnerable plaque). There is a 6 times greater risk of stroke in people with IPH! For those who were reluctant to consider it, they expressed that it was mostly due to their concerns for the relative cost and current wait time for MRI. 

Unfortunately, the response rate for this online survey was very low. Reasons given for the reluctance to participate were that physicians were on a tight schedule and were busy with their patients. Feedback from participants was that the online survey seemed long. Nevertheless, from the responses received, we were able to learn more about physicians’ perspectives of using MRI for carotid artery stenosis diagnosis and assessment.

In the end, it was an exciting and valuable experience to plan out and execute this research project. Most importantly, I had the pleasure to join Dr. Tyrrell’s lab and meet his team. I am grateful for all the help and support which I have received throughout my time at the lab. I look forward to continuing to work as a member of Dr. Tyrrell’s lab.

Stella Bing

Back to Basics… Midpoint Thoughts from an ROP Student

Reaching new heights? (Source: NYT)

Through the ‘Research Opportunity Program‘ (ROP) for second year students at U of T, I have been working on a project about physicians’ willingness to use MRI as the front-line diagnostic imaging technology for carotid stenosis patients. For a description see here.

After a recent discussion with Dr. Tyrrell (my supervisor), and as I approach the midpoint of my ROP project, I thought it would be a good idea to review some of my background knowledge of carotid stenosis from my work in the Fall term. Having a certain amount of independence while working on this project has been a great experience, but it also means I am responsible for keeping track of my own learning.


So, during the first week of January, I took out my notes, my Physiology textbook, and several articles in order to compile what I have learned so far and highlight areas that need further review.

Review in process!

Begrudgingly, I’ll admit that this ‘self-directed’ review process has shed new light on the usefulness of midterms in other courses. However, I still prefer this project-based review format. It has allowed me to review necessary information to make sure that it is fresh in my mind. Now I feel more prepared to begin the second half of the project. I’m looking forward to a major meeting this month and all the other exciting parts of the project to come.


Julia Robson

Ethics Schmethics?

 

Today, it may seem obvious that the first step of any research project should be to complete a proposal for ethics review. But why do we need ethical standards? While helping to complete an ethics form for a project I’m working on, I wondered if scientists perhaps made more ‘progress’ before ethical considerations became commonplace. Even if this was the case, research is certainly better now, when institutions and procedures protect patients’ and research subjects’ rights. 

It also seems that scientific research in the 18th and 19th centuries tended to be somewhat more haphazard than it is now, and almost certainly less ethical. For example, Dr. Edward Jenner tested his smallpox inoculation hypothesis for the first time on an eight-year-old
boy in 1796, with little preliminary understanding and no certainty that the patient would not be severely harmed.

Scientists were often fairly independent, acting based on their own curiosity to advance knowledge. Fortunately, research standards have evolved significantly since then. Ethics have been a major part of the transition, as ethical standards help to ensure that scientific research does not cause harm to researchers or subjects. The shocking Stanford Prison Experiment, just one example, shows that physical and psychological damage can occur if study participants’ rights are not upheld through ethics. College students with no criminal record were asked to play the role of prisoners and prison guards, the ‘guards’ became brutal and cruel, while the ‘prisoners’ became stressed and depressed. The experiment was terminated early, after only six days.

Fortunately, much has changed since the emergence of modern science in the 20th century. The current structure of research, including working in teams and undergoing peer review, helps to ensure a high standard of practice. Nevertheless, ethical issues in science remain. Researchers who work with human participants can become quite focused on the minutiae of their work, so Research Ethics Boards have an important mediating role. They provide an experienced, unbiased viewpoint that weighs the potential benefits of the research against any harm that may come to participants. Even if an ethical review sometimes slows the pace of scientific progress, it provides an essential foundation and structure for research, to the benefit of participants and researchers alike.  





Julia Robson

2nd year student at U of T

All the World’s a Stage

For journalists, authors, bloggers and tweeters, sharing articles has never been easier. Indeed, the public expects to be able to read articles about world events almost in real-time. For example,
the New York Times Twitter account was updated nine minutes ago
, and National Geographic tweeted three minutes ago. This expectation of speediness applies equally to scientific advances as it does to international affairs.
As an avid reader of online news, I would be the last to complain about being able to access such a vast amount of information. But there is something particularly noteworthy about information presented by a visible human. Perhaps that explains the persistence of televised news in the age of Twitter. 

Maybe it also explains the popularity of other media sources like TED talks, which often explain complex ideas in an engaging and understandable format. A personal favourite is “The best stats you’ve ever seen” by Hans Rosling. In his talk, Rosling explains the importance of little-known global public health data that shows the progress (or lack thereof) made by different countries over the past few decades. 

A more recent talk on a similar topic is also informative. One would be hard-pressed to find a paper or article that presents the same information with as much clarity and appeal.

In addition to numerous (maybe too numerous?!) TED talks, I have recently experienced the value of human-to-human information transfer. At the beginning of my ROP project in September, I was lucky to be able to hear about previous students’ research in person. I think it helped address the complexity of the work, but also conveyed its importance and the effort that had gone into it. Thanks Kiersten!
I’m not sure if information is generally more effective this way, but it is almost certainly more memorable. In any case, it has definitely worked for the 3.5 million subscribers to CrashCourse’s YouTube channel, where one can learn about anything from astronomy to macroeconomics.
For me, learning more about how researchers give and receive qualitative information to and from their subjects has allowed for a more well-rounded understanding of information transmission in the digital age.  But I think researchers andthe media have a lot to learn from each other. Communication is key for both, so understanding how others best absorb and respond to information can be instrumental.
That’s all for now, Julia!

Helena Lan: Summer 2014 ROP

Helena Lan Summer 2014 ROP

What is research like? If you had asked me this
question several months ago, I would have answered, “You wear a lab coat and
goggles while mixing chemicals or observing organisms. Hopefully something
interesting will happen, so that you get to publish your findings!” Well, after
participating in the Research Opportunity Program (ROP) at the University of
Toronto, I discovered that medical imaging research is more than just
pipetting, and is all the more exciting!

 
So what kind of research is conducted in the medical imaging world? For my ROP, the objective of my project was to evaluate the roles of the non-invasive imaging modalities for diagnosing carotid stenosis. Hence, I engaged in online literature research of the various imaging techniques for assessing this disease. In this process, I also learned to use Zotero to manage all my references, which provides an easy way to generate a bibliography (when the software doesn’t crash every time you open it). After gathering all the pertinent information, I then put together a review article suggesting how a change in the current imaging approach could potentially improve clinical outcome. Who knew a report could be compiled without doing the lab grunt work?     
 
Wait, so this is all a radiologist does? Sitting in front of a computer and typing all day? Of course not! During our time at Sunnybrook Hospital, we got the chance to chat with a radiologist and discovered that she could decide whether patients should be released after taking a look at their diagnostic images. Pretty powerful, eh? That’s not all. We also found out how radiologists identified any abnormalities in patients, as we had the opportunity to work with the VesselMass software which allowed for the delineation of the lumen and vessel wall of arteries on MRI images. Oh, and did I mention we observed an MRI and an ultrasound examination of the carotid arteries, and even got to perform an ultrasound scan ourselves. Super cool!
 
Still craving for more of my ROP experience? Check out my timeline infographic! You will find all the things I learned and all the fun I had there. Last but not least, I’d like to shout out a big THANK YOU to Prof. Pascal Tyrrell and Dr. Eli Lechtman, who guided us every step of the
way. Also, I’m very grateful to Dr. Alan Moody for including us in his research program at Sunnybrook, as well as other members of the VBIRG group who gave us the chance to
participate in various activities. My summer would not have been this fun and meaningful without all of your help!
 
Have fun researching,


Helena Lan
 

A YSP Student Perspective: MRI and Carotid Artery Disease

Hershel Stark, MED YSP 2014 Student

Throughout the month of July, I participated in a research program with the Division of Teaching Laboratories within the Faculty of Medicine at the University of Toronto. I was assigned to work with Prof. Pascal
Tyrrell and the Department of Medical Imaging, and spent the majority of my time with the Vascular Biology Imaging Research Group (VBIRG) at Sunnybrook Research Institute. I would like to discuss my experiences, what I gained from the program, and how I can take those skills with me into the future.



Essentially, the program was composed of presentations and shadowing opportunities in which I was introduced to various imaging modalities used in both the clinical and research fields. I primarily studied MR imaging, but was nevertheless exposed to other modalities including ultrasound and CT.  Towards the end of the program, I had two principal objectives: to present my experiences to the VBIRG group and to design an infographic for displaying. Below is a copy of my infographic:

Notwithstanding the abundance of knowledge I gained from studying the subject content, I acquired a variety of essential research skills by partaking in the program. Shadowing proficient researchers as they collected
and analyzed data provided me with a thorough insight of a researcher’s methods and techniques. The researchers that I worked with appropriately explained their individual roles on the research team, which led to my understanding of the significance of collaboration in scientific and medical research.
One last aspect of the program that I would like to address is the daily workshops that were conducted by two instructors from the Division of Teaching Laboratories, Jastaran Singh and Jabir Mohamed. Each of these brief workshops focused on an important general topic relevant to research in general, ranging from discussing common scientific practices to elaborating on literary research. I believe that the combination of skills and knowledge that I obtained from all elements of the program will be useful in my potential
research career in university.
 Lastly, I would like to take this opportunity to formally thank all of those that contributed to making the program a truly enjoyable and intellectually stimulating experience. I would like to extend my gratitude to
Dr. Alan Moody and the members of the VBIRG group for allowing me to shadow their research projects, as well as to Prof. Pascal Tyrrell and the Department of Medical Imaging at U of T for constructing the program and offering much assistance in the formation of my infographic. Finally, I’d like to thank Dr. Chris Perumalla and the Division of Teaching Laboratories in the Faculty of Medicine at U of T for formulating the research module of the Youth Summer Program, and Jastaran Singh and Jabir Mohamed for providing guidance as instructors throughout the program.
Best of luck in all of your future endeavours,
Hershel Stark