Siddharth Srinivasan Iyer

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I am a graduate student in Electrical Engineering and Computer Science at the Massachusetts Institute of Technology. I got my undergraduate degree at the University of California, Berkeley.

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Research

I am interested in acquisition and reconstruction problems in Magnetic Resonance Imaging (MRI). I am currently advised by Professor Kawin Setsompop. In Berkeley, I worked under the guidance of Professor Michael Lustig.

PhysiCal: A rapid calibration scan for B0, B1+, coil sensitivity and Eddy current mapping.
Siddharth Srinivasan Iyer, Congyu Liao (廖聪裕), Qing Li, Mary Kate Manhard, Avery Berman, Berkin Bilgic and Kawin Setsompop.
In Proceedings of the International Society for Magnetic Resonance in Medicine, 2020.

Abstract. Calibration scans that acquire coil sensitivity, B0, and B1+ inhomogeneities information play an important role in enabling modern acquisition and reconstruction techniques. This work proposes a unified, rapid calibration sequence termed Physics Calibration (PhysiCal) to obtain accurate B0, Eddy, B1+ and coil sensitivity maps. PhysiCal utilizes a carefully designed mix of full and variable density sampling acquisitions across echoes with synergistic constrained and eigenvalue reconstruction for robust and accurate recovery of whole-brain B0, B1+, Eddy and 32-channel coil sensitivity maps in just 11 seconds at 1 mm x 2 mm x 2mm resolution at 3T.

Summa Cum Laude awarded.

Links:   Abstract  /  Talk coming soon.   

Rapid, Time-Resolved Brain Imaging with Multiple Clinical Contrasts using Wave-Shuffling.
Siddharth Srinivasan Iyer, Daniel Polak, Congyu Liao (廖聪裕), Stephen Cauley, Berkin Bilgic and Kawin Setsompop.
In Proceedings of the International Society for Magnetic Resonance in Medicine, 2019.

Abstract. Previously, we presented Wave-Shuffling: a technique that combines random-sampling and the temporal low-rank priors of Shuffling with the sinusoidal gradients of Wave-CAIPI to achieve highly-accelerated, time-resolved acquisitions. In this work, we optimize and apply Wave-Shuffling to T2-SPACE and MPRAGE to achieve rapid, 1 mm-isotropic resolution, time-resolved imaging of the brain where we recover a time-series of clinical contrast. We also present preliminary explorations into Joint-Contrast Wave-Shuffling to boost signal-to-noise ratio and reconstruction-conditioning at high accelerations.

Magma Cum Laude awarded.

Links:   Abstract  /  Talk   

Faster (T2-)Shuffling With Wave-Encoding
Siddharth Srinivasan Iyer, Berkin Bilgic and Kawin Setsompop.
In Proceedings of the International Society for Magnetic Resonance in Medicine, 2018.

Abstract. T2-shuffling is a recently proposed approach that can reconstruct multiple, sharp T2-weighted images from a single fast spin-echo (FSE) scan. Wave-CAIPI is a parallel imaging technique that uses additional sinusoidal gradients to spread aliasing in the readout direction, to take full advantage of coil-sensitivity information in highly accelerated rectilinear acquisitions. In this work, we augment T2-shuffling with wave-encoding and examine the ability of this combined approach in accelerating FSE acquisition that can achieve multiple T2-weighted images reconstruction. We demonstrate the efficacy of our technique through a 2D simulation, where wave-encoding was shown to provide good reconstruction at 2-3x higher accelerations.

Links:   Abstract  /  Talk   

Towards A Parameter Free ESPIRiT: Soft Weighting For Robust Coil Sensitivity Estimation.
Siddharth Srinivasan Iyer, Frank Ong and Michael Lustig.
In Proceedings of the International Society for Magnetic Resonance in Medicine, 2016.
Published at Magnetic Resonance in Medicine, 2020.

Abstract. ESPIRiT is a robust, auto-calibrating approach to parallel MR image reconstruction that estimates the subspace of sensitivity maps using an eigenvalue-based method. While it is robust to a range of parameter choices, having parameters that result in a tight subspace yields the best performance. We propose an automatic, parameter free method that appropriately weights the subspace using a shrinkage operator derived from Stein's Unbiased Risk Estimate. We demonstrate the efficacy of our technique by showing superior map estimation without user intervention in simulation and in-vivo data compared to the current default method of subspace estimation.

Summa Cum Laude awarded.

Links:   Abstract  /  Talk  /  Preprint  /  Publication   

T2 Shuffling - Dynamic MRI Dimensionality Reduction
Siddharth Srinivasan Iyer, Jon Tamir and Michael Lustig.

Abstract. MRI is a safe and powerful tool that can be used to image both anatomy and function. Acquiring 3D MRI over time has several clinical applications:

  • Reduce image blur from conventional 3D acquisition.
  • Visualize signal behavior over time.
  • Quantify tissue parameters in anatomy.
We aim to find a robust and low-dimensional representation of the dynamic images.

Link:  Poster   


Teaching

EE16B: Designing Information Devices and Systems II, Spring 2017
University of California, Berkeley

  • Co-head content TA with Brian Kilberg.
  • Some videos notes (as a YouTube playlist) made by me and fellow TA Saavan Patel: here.
  • Teaching evaluations: here.


EE16B: Designing Information Devices and Systems II, Fall 2016
University of California, Berkeley

  • Discussion and content TA.
  • Some videos notes (as a YouTube playlist) made by me and fellow TA Saavan Patel: here.
  • Draft supplemental linear algebra notes I've written: here.
  • Teaching evaluations: here.


EE16B: Designing Information Devices and Systems II, Spring 2016
University of California, Berkeley

  • Discussion and content TA.
  • Teaching evaluations: here.



Website template borrowed and modified from Jon Barron.
Last updated: September 2020.