Paper accepted at MICCAI 2019 CLIP Workshop

16th August, 2019

Our paper on "Recovering physiological changes in nasal anatomy with confidence estimates" was accepted for oral presentation at the MICCAI 2019 CLIP workshop. We will be presenting this work on October 17th, the last day of the conference. Paper and talk will be available here soon!

Starting at Philips Research!

22nd July, 2019

I am very excited to announce that I will be joining Philips Research as a Scientist in the Image-Guided Therapy team starting August of this year! I am looking forward to shifting focus to different image modalities and image-guided procedures. Lots to learn. Updates to follow.

Starting role as faculty member at LCSR

4th June, 2019

I'm excited to announce that I am moving up from Provost's Postdoctoral Fellow to research faculty as an Assistant Research Scientist in the Laboratory for Computational Sensing and Robotics at the Johns Hopkins University! Looking forward to this new role and publishing more papers. I plan to move my focus toward learning meaningful representations of medical data in an unsupervised way. Specifically, my focus will be to learn representations that can help disentangle endoscopic camera motion and tool motion without any labels.

IJCARS - MICCAI 2018 Special Issue paper accepted!

22nd May, 2019

Our journal extension of our MICCAI 2018 publication "Endoscopic navigation in the clinic: registration in the absence of preoperative imaging" is accepted in the IJCARS - MICCAI 2018 Special Issue. This paper explores the ability of our deformable registration algorithms to associate confidence measures with their computation allowing users to modulate their trust in systems using our algorithms to provide surgical navigation. Our code is available here.

MedIA paper accepted!

30th April, 2019

Our paper on the deformable most-likely-point registration paradigm is accepted in the journal Medical Image Analysis. This paper presents an extensible framework for deformable registrations based on statistical models of variance in anatomy. We also present and evaluate three algorithms developed within this framework that use different features and noise models. Our code is available here.

Abstracts accepted at SAGES 2019 meeting!

1st Feb, 2019

Our two abstracts submitted to the Society of American Gastrointestinal and Endoscopic Surgeons 2019 Meeting to be held in Baltimore, MD have been accepted! Our first abstract is about camera pose estimation directly from video in order to automatically initialize video-based registration algorithms. Our second abstract is about learning to disentangle modes in surgical video data in an unsupervised way.

Awarded the NVIDIA GPU Grant!

20th Nov, 2018

Excited to announce that we were awarded the NVIDIA GPU Grant! We will pursue our work toward automatically initializing registration algorithms. We will use the GPU to render synthetic endoscopic video data with ground truth and also to learn camera pose from the video frames!

Endoscopic navigation without CT paper presented at MICCAI!

19th Sept, 2018

Our paper, Endoscopic navigation in the absence of CT imaging, was presented at MICCAI in Granada, Spain! The talk was presented during the CAI session in the García Lorca Hall and a poster presentation followed the oral session.

Our desnse depth estimation paper by Xingtong Liu wins best paper and best presentation awards!

16th Sept, 2018

PhD student Xingtong Liu presented our paper, Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy, at the CARE (Computer Assisted and Robotic Endoscopy) Workshop at MICCAI in Granada, Spain. This paper was awarded the best paper award at the workshop and the presentation was voted the best presentation.

MICCAI paper selected for oral presentation and travel award!

28th July, 2018

Our MICCAI paper Endoscopic navigation in the absence of CT imaging is selected for oral presentation in Granada, Spain! It also earned a travel award based on reviewers' scores. We will update this space with information about the day and time of the presentation as we learn more! Slides wil be available on this website after the talk.

The talk will be presented on the 19th of September at 9:45am in the García Lorca Hall.

Deformable registration code now available!

20th July, 2018

Codebase with implementations of most-likely point and deformable most-likely point algorithms is now available on github. This includes code for our MICCAI paper Endoscopic navigation in the absence of CT imaging. An extensive README will walk you through the steps to install dependencies and our codebase as well as steps to run a test script to ensure everything works as expected!

Paper accepted to MICCAI workshop CARE!

19th July, 2018

Our paper, "Self-supervised Learning for Dense Depth Estimation in Monocular Endoscopy", by Xingtong Liu was accepted at MICCAI workshop on Computer Assisted Robotic Endoscopy (CARE). This paper explores the use of structure from motion and depth consistency among frames to predict dense depth maps from single frames in sinus endoscopy. Preprint is available!

Selected to attend Rising Stars in Biomedical!

5th July, 2018

I will attend Rising Stars in Biomedical, a two-day career development workshop, after being nominated by a montor and selected from a pool of outstanding candidates. The workshop, organized by JHU and MIT faculty, aims to connect top junior researchers in the biomedical field. I will get a chance to present my work to other participants and faculty and also to network with peers in both academia and industry.

MICCAI preprint is now available!

11th June, 2018

Preprint of our paper, Endoscopic navigation in the absence of CT imaging, is now available on arXiv. Read to find out how navigation during minimally invasive procedures is possible even when corresponding patient CT scans are not available.

Paper accepted to MICCAI!

25th May, 2018

Our paper, "Endoscopic navigation in the absence of CT imaging", was accepted at MICCAI. This paper presents a method that enables navigation in the absence of patient specific CTs by registering video features to a statistical shape model built from population CTs. This paper also computes statistical confidence in each registration allowing clinicians to know when the system can be trusted.

IEEE TMI preprint is out!

8th May, 2018

Preprint of our paper, Evaluation and Stability Analysis of Video-Based Navigation System for Functional Endoscopic Sinus Surgery on In-Vivo Clinical Data, is now available in the Early Access section of IEEE TMI. Read to learn about video-CT registration with stability analysis for endoscopic procedures!

Paper accepted to IEEE TMI!

28th April, 2018

Our paper, "Evaluation and Stability Analysis of Video-Based Navigation System for Functional Endoscopic Sinus Surgery on In-Vivo Clinical Data", was accepted for publication by IEEE TMI. This paper presents a pipeline for rigid video-CT registration that produces submillimeter registrations and also performs a stability analysis for the registration. This allows a clinician to gauge the reliability of the computed registration. Watch this space for the published paper!

Thesis is submitted!

13th April, 2018

My thesis, "Deformable registration using shape statistics with applications in sinus surgery", was accepted by the library at the Johns Hopkins University. The thesis will be published at the end of the academic year, and I will be hooded at the graduation ceremony in May. The thesis will be available here as soon as it is published. Hold tight!

Done with dissertation defense!

22nd March, 2018

Successfully defended my dissertation! My talk presented some of our latest work on deformable registration using statistical shape models. The talk was attended by my thesis committee consisting of Russ Taylor, Greg Hager, Austin Reiter and Masaru Ishii, as well as by colleagues and friends. I had a great time sharing my work with everyone, and hope to continue to do so. Code from my registration framework will be available soon, as well as slides from my defense. Watch this space for more!

Awarded the Provost's Postdoctoral Fellowship

5th Feb, 2018

Named one of 7 Provost's Postdoctoral Fellows for the year 2018. This is a great opportunity for me to continue my work at the Johns Hopkins University once I have completed my Ph.D. This fellowship is part of the Faculty Diversity Initiative, which is one of many programs outlined in the JHU Roadmap on Diversity and Inclusion. All fellows receive ne year of salary at the current NIH level of support to continue work in academia. For more information, visit the program page. The fellows named can be found here.

Two new journal papers submitted to start off 2018!

15th Jan, 2018

Two new papers on registration techniques have been submitted to two different journals for review by our team. One of the papers is a rigid registration paper led by Simon Leonard, while the other is my effort towards a deformable registration framework. Watch this space for updates as the papers are published and we are able to share more!

PhD student profiles up on CS department website!

3rd Oct, 2017

The Department of Computer Science at the Johns Hopkins University released a PhD student profile page highlighting student research areas and publications allowing people to learn more about the variety of work being done here. A recent PhD graduates profile page is also available to learn where Johns Hopkins CS PhD students go after graduation!

Volunteered with Johns Hopkins Engineering Innovation program!

18th July, 2017

Volunteered with Johns Hopkins Engineering Innovation program to help with an activity designed by Anand Malpani to teach high school students about the role of technology in surgical education. The students came from all around the world, and learned about the various robotic skills required in open and laproscopic surgery.

Video from the "Simultaneous segmentation and correspondence improvement using statistical modes" talk is out now!

1st May, 2017

Video of my presentation of our paper simultaneous segmentation and correspondence improvement using statistical modes at SPIE Medical Imaging conference earlier this year is out now! This paper was selected as one of the Robert F. Wagner best student paper finalists, and presents an elegant method to simultaneously improve segmentation and correspondence between homologous meshes.

Inducted into Upsilon Pi Epsilon (UPE)!

29th March, 2017

Was inducted into the International Honor Society for the Computing and Information Disciplines, Upsilon Pi Epsilon (UPE). UPE is the first honor society dedicated to the discipline of computer information systems and computer science.

"Simultaneous segmentation and correspondence improvement using statistical modes" is out now!

23rd March, 2017

Our paper, simultaneous segmentation and correspondence improvement using statistical modes, Robert F. Wagner best student paper finalist, is out now and available for download from the SPIE Digital Library. In this paper, we present a method that iteratively improves both segmentation as well as correspondence between segmentations by using statistical shape models (SSMs) not only to improve correspondence, but also to constrain the movement of vertices during segmentation improvement. To learn more, take a look at the publication! If you do not have a subscription to the SPIE Digital Library, feel free to contact me for a copy of the paper!

SPIE paper is a Robert F. Wagner best student paper finalist

18th January, 2017

Our paper, Simultaneous segmentation and correspondence improvement using statistical modes, which was accepted to SPIE Medical Imaging conference, is a Robert F. Wagner best student paper finalist. All finalists will be announced and recognised at the start of the Plenary and Awards session on Monday, 13th February, at 4pm in Orlando, FL. The runner-up and winner will be announced after this!

The winner and runner-up for the Robert F. Wagner best student paper award were announced at the conference on Monday, the 13th of February. More inforamtion and updates can be found here.

Geodesics using Waves: Computing Distances using Wave Propagation

9th December, 2016

Master's project manuscript is now public! In this paper, we present a new method for computing approximate geodesic distances. We introduce the wave method for approximating geodesic distances from a point on a manifold mesh. Our method involves the solution of two linear systems of equations. One system of equations is solved repeatedly to propagate the wave on the entire mesh, and one system is solved once after wave propagation is complete in order to compute the approximate geodesic distances up to an additive constant. However, these systems need to be pre-factored only once, and can be solved efficiently at each iteration. All of our tests required approximately between 300 and 400 iterations, which were completed in a few seconds. Therefore, this method can approximate geodesic distances quickly, and the approximation is highly accurate. Watch videos about the project on the project page!

Panelist at the GRACE Mentoring Dinner

5th December, 2016

Served on the panel of the GRACE Mentoring Dinner along with Prof. Joanne Selinksi, Prof. Muyinatu Bell, Dr. Louise Sengupta, and undergraduate CS student, Paige Senal. The event, organized by GRACE in Clipper Room, Shriver Hall on the 5th of December, was attended by over 90 people. We discussed our experiences in our fields, as well as issues faced by women in engineering and how we can combat them. You can read more about the event here.

Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm

19th October, 2016

Presented our paper Anatomically Constrained Video-CT Registration via the V-IMLOP Algorithm at MICCAI in Athens, Greece. In this paper, we present an algorithm developed to aid surgeons during functional endoscopic sinus surgery (FESS). FESS is a surgical procedure used to treat acute cases of sinusitis and other sinus diseases. FESS is fast becoming the preferred choice of treatment due to its minimally invasive nature. However, due to the limited field of view of the endoscope, surgeons rely on navigation systems to guide them within the nasal cavity. State of the art navigation systems report registration accuracy of over 1mm, which is large compared to the size of the nasal airways. We present an anatomically constrained video-CT registration algorithm that incorporates multiple video features. Our algorithm is robust in the presence of outliers. We also test our algorithm on simulated and in-vivo data, and test its accuracy against degrading initializations. The manuscript is also available on arxiv, and the code is coming soon. Read more on the project page!

Paper accepted for oral presentation at SPIE Medical Imaging conference

10th October, 2016

Our paper, Simultaneous segmentation and correspondence improvement using statistical modes, has been accepted for an oral presentation at SPIE Medical Imaging conference in Orlando, FL, from the 12th-16th of February, 2017. The talk will be held on the 14th of February. Please join!