Ayushi Sinha

I am a Ph.D. candidate at the Johns Hopkins University, working with Greg Hager and Russ Taylor. I work in the areas of medical image computing and analysis in the Department of Computer Science. My research interests lie specifically in segmentation and statistical analysis of anatomical structures, and registration. I am currently working on building statistical models of structures in the paranasal sinuses and nasal airway, and on using this statistical information to improve video-CT registration to enhance endoscopic navigation during sinus surgery as well as other minimally invasive surgeries through the sinus. I received a Bachelor in Science degree in Computer Science, and a Bachelor in Arts degree in Mathematics from Providence College. I received a Master of Science in Engineering in Computer Science at the Johns Hopkins University, advised by Misha Kazhdan.



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News

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! Read more...


Geodesics using Waves: Computing Distances using Wave Propagation

9th December, 2016

Master's project manuscript is now public! Read more...


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. Read more...



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Research

For a more detailed list of projects, check out my LinkedIn page.

Enhanced Endoscopic Navigation

We are working on building statistical models of the sinus, and using these models to improve video-CT registration to improve intra-operative navigation. For more information, go here.

Geodesics using Waves

We used properties of wave propagation to efficiently estimate geodesics on manifold surfaces. Our estimations are reliable, and are computed quickly. These geodesics can be used in several applications. For more information, go here.

Open Connectome Project

A connectome is a high resolution graph of the brain, where each vertex of the graph is a neuron in the brain, and each edge is a synapse. We are working on automatically annotating and tracking all neurons and synapses. For more information, go here.

Genome Resequencing using Signal Processing

We used fast fourier transforms to achieve fast and accurate genome alignment and in other sequencing data analyses. This project started in Yanif Ahmed's Big Data, Small Languages, Scalable Systems course, and continued in Ben Langmead's Frontiers of Sequencing Data Analysis course, both taught at JHU. For more information, go here.

3D Reconstruction of Hopkins Landmark

We computed a 3D reconstruction of a Hopkins landmark from 2 images of the same as part of the final project for Nicolas Padoy's Computer Vision course at the Johns Hopkins University. A demo video showing our results was voted the best computer vision project video in 3D reconstruction. For more information, go here.

Sorting using CUDA

We compared sorting algorithms inplemented in parallel on NVIDIA's parallel programming architechture, CUDA. This project was undertaken as part of a Research Experience for Undergraduates (REU) program at Washington University in St. Louis, MO during the summer before my senior year of undergraduate studies. For more information, go here.

Publications

Get more information on my Google Scholar page, or check out my CV.

A Sinha, A. Reiter, S Leonard, M Ishii, RH Taylor, GD Hager
Simultaneous segmentation and correspondence improvement using statistical modes
SPIE Medical Imaging, Orlando, FL. 2017. (Accepted).
Robert F. Wagner Best Student Paper Award Finalist, 2017

Seth D. Billings, A Sinha, A. Reiter, S Leonard, M Ishii, GD Hager, RH Taylor
Anatomically constrained Video-CT registration via the V-IMLOP algorithm
MICCAI, Athens, Greece. 2016.
Proceedings in Medical Image Computing and Computer-Assisted Intervension -- MICCAI 2016,
19th International Conference, Athens, Greece, October 17-21, 2016, Proceedings, Part III. Vol. 9902: pp. 133-141


A Sinha, S Leonard, A Reiter, M Ishii, RH Taylor, GD Hager
Automatic segmentation and statistical shape modeling of the paranasal sinuses to estimate natural variations
SPIE Medical Imaging, San Diego, CA. 2016.
Proceedings in SPIE Digital Library, Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97840D (March 21, 2016)

S Leonard, A Reiter, A Sinha, M Ishii, RH Taylor, GD Hager
Image-based navigation for functional endoscopic sinus surgery using structure from motion
SPIE Medical Imaging, San Diego, CA. 2016.
Proceedings in SPIE Digital Library, Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 97840V (March 21, 2016)

A Reiter, S Leonard, A Sinha, M Ishii, RH Taylor, GD Hager
Endoscopic-CT: learning-based photometric reconstruction for endoscopic sinus surgery
SPIE Medical Imaging, San Diego, CA. 2016.
Proceedings in SPIE Digital Library, Proc. SPIE 9784, Medical Imaging 2016: Image Processing, 978418 (March 21, 2016)

A Sinha, WG Roncal, N Kasthuri, JW Lichtman, R Burns
Automatic Annotation of 3D Axoplasmic Reticula for Neuron Segmentation
Resting State Brain Connectivity, Boston/Cambridge, MA. 2014.
Proceedings in Brain Connectivity, Vol. 4(9): pp. A26 (November 21, 2014)

A Sinha, M Kazhdan
Geodesics using Waves: Computing Distances using Wave Propagation
The Johns Hopkins University, Baltimore, MD. 2014.
Submitted as Master's project (May 21, 2014)

A Sinha, WG Roncal, N Kasthuri, JW Lichtman, R Burns, M Kazhdan
Automatic Annotation of Axoplasmic Reticula in Pursuit of Connectomes using High Resolution Neural EM Data
Hopkins Imaging Conference, Baltimore, MD (November 21, 2013)

A Sinha
Sorting on CUDA
Annual Celebration of Student Scholarship and Creativity, Providence, RI (April 13, 2011)


Talks

Videos will not work in the PDF slides. For videos, contact me!



Experience

Teaching

Computer Vision (September, 2012 - December, 2012)

Teaching Assistant @ The Johns Hopkins University


Computer Graphics (January, 2012 - May, 2012)

Teaching Assistant @ The Johns Hopkins University


Computer Systems Fundamentals (September, 2011 - December, 2011)

Teaching Assistant @ The Johns Hopkins University


Computer Science Tutor (January, 2011 - May, 2011)

Providence College


Mathematics Tutor (January, 2008 - May, 2011)

Providence College



Industry

Intel Corporation (May, 2013 - August, 2013)

Graphics Graduate Technical Intern

I worked on parallelizing algorithms to process High Dynamic Range (HDR) images on Intel processors, as well as on offline compilation of OpenCL kernels for parallel processing.

Miscellaneous

Tennis

Keep an eye on my college tennis team here:

PCWT


And details about my career with Providence College Women's Tennis here:
PCWT Ayushi

Photography

Some pictures I have taken over the years:



And more can be found here:

VSCO Grid


Contact Me

If you have any questions, you can stop by my desk or shoot me an email.

Department of Computer Science
The Johns Hopkins University
160 Malone Hall
3400 N. Charles St.
Baltimore MD 21218-2608

Desk

340 Malone Hall

Email

asinha8(at)jhu(dot)edu

Phone (Work)

410-516-8775

Affiliations