People

Alejandro Sisniega-Crespo, PhD

Research Associate

Office: Traylor 622
Lab: The I-STAR Lab

asisniega@jhu.edu


Education

PhD, Biomedical Engineering, Universidad Carlos III de Madrid, 2013
BSc, Electrical Engineering, Universidad Politecnica de Madrid, 2006

Research Interests

Dr. Sisniega’s research background builds on the design of multimodality high-resolution imaging systems for small animal imaging (PET-CT, SPECT-CT, and FDOT-CT), for which Dr. Sisniega played a significant role in the design, development, and optimization of the high-resolution Cone-Beam CT (CBCT) component of the imaging system. His expertise includes system design and characterization through analytical modeling and Monte Carlo simulation techniques using GPU-based parallelization, and algorithm design for CBCT image processing, artifact compensation and 3D model-based image reconstruction.

His current work is focused on improvement of image quality in cone-beam CT through algorithmic approaches for: i) high-fidelity, high-speed, artifact correction, ii) volumetric image reconstruction methods for mitigation of noise and sparse sampling effects, and iii) acceleration of optimization methods to bring advanced model-based iterative reconstruction to runtimes acceptable for clinical practice. This work comprises comprehensive artifact correction methods in soft-tissue CBCT (with application to brain imaging in traumatic brain injury scenarios), including compensation of detector non-idealities, model-based beam-hardening correction, and high-fidelity, high-speed Monte Carlo scatter correction, leveraging variance reduction and GPU parallelization to achieve competitive runtime in clinical scenarios. His last research investigated approaches for purely image-based patient motion compensation in dedicated CBCT of the extremities (undergoing rigid motion) and in more challenging scenarios involving automatic compensation of deformable motion in soft-tissue CBCT.

Publications Search

From Pub Med   |   Google Scholar Profile